diff --git a/.github/workflows/validate.yml b/.github/workflows/validate.yml index 3be031f..2982ac7 100644 --- a/.github/workflows/validate.yml +++ b/.github/workflows/validate.yml @@ -22,3 +22,25 @@ jobs: run: python -m pip install -r requirements-dev.txt - name: Validate catalog and generated files run: make check + + website: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1 + - uses: actions/setup-node@820762786026740c76f36085b0efc47a31fe5020 # v7.0.0 + with: + node-version: "22" + cache: npm + cache-dependency-path: website/package-lock.json + - name: Install website dependencies + working-directory: website + run: npm ci + - name: Lint website + working-directory: website + run: npm run lint + - name: Build and test website + working-directory: website + run: npm test + - name: Audit production dependencies + working-directory: website + run: npm audit --omit=dev --audit-level=high diff --git a/AGENTS.md b/AGENTS.md index ee1b564..b8c8ef1 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -2,7 +2,7 @@ ## Source of truth -- Edit `data/papers.yaml`; do not hand-edit generated catalog tables, `data/papers.json`, `papers/*.md`, or `views/*.md`. +- Edit `data/papers.yaml`; do not hand-edit generated catalog tables, `data/papers.json`, `website/data/catalog.json`, `papers/*.md`, or `views/*.md`. - Update `data/schema.json` and `docs/taxonomy.md` together when adding fields, products, statuses, or method tags. - A product mention means the complete agent or harness, not merely a model from the same vendor. @@ -20,6 +20,9 @@ python -m pip install -r requirements-dev.txt make build make check +npm --prefix website install +make site-check ``` Run `make build` after catalog edits and include all generated changes in the same commit. +The website reads the generated `website/data/catalog.json`; never maintain a second paper list in the frontend. diff --git a/CHANGELOG.md b/CHANGELOG.md index 91e8919..4b7186f 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -4,6 +4,13 @@ All notable catalog and schema changes are recorded here. ## [Unreleased] +### Added + +- Interactive bilingual research catalog with full-text search and product, evidence, fairness, venue, and method filters +- Expandable paper evidence dossiers and recurring-method summaries +- Host-aware social sharing metadata and a dedicated Open Graph card +- Website build, server-rendering, catalog-parity, lint, and dependency-audit checks in CI + ### Planned - Deeper audits of product versions, model snapshots, and execution budgets diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index cd4029d..ab950ea 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -33,10 +33,10 @@ same_budget: unknown 3. Record authors, identifiers, system name, artifact status, and publication date from primary sources. 4. Choose the narrowest correct evidence class and comparison scope. 5. Record where the supporting result appears in the paper. -6. Run `make build` to regenerate READMEs, JSON, views, and paper dossiers. -7. Run `make check` before opening a pull request. +6. Run `make build` to regenerate READMEs, both JSON exports, views, and paper dossiers. +7. Run `make check` and `make site-check` before opening a pull request. -Do not manually edit content between `CATALOG:*:START` and `CATALOG:*:END` markers in either README. Files under `papers/` and `views/`, plus `data/papers.json`, are also generated. +Do not manually edit content between `CATALOG:*:START` and `CATALOG:*:END` markers in either README. Files under `papers/` and `views/`, plus `data/papers.json` and `website/data/catalog.json`, are also generated. ## Required source checks @@ -73,4 +73,5 @@ Future products must be added to both `data/schema.json` and `docs/taxonomy.md` - [ ] The evidence location and comparison scope are recorded. - [ ] Comparison caveats are explicit. - [ ] `make check` passes. +- [ ] `make site-check` passes when the website or catalog changed. - [ ] No copyrighted PDF has been committed. diff --git a/Makefile b/Makefile index a1f362e..40cf3ad 100644 --- a/Makefile +++ b/Makefile @@ -1,4 +1,4 @@ -.PHONY: install build validate test lint check +.PHONY: install build validate test lint check site-check install: python -m pip install -r requirements-dev.txt @@ -22,3 +22,8 @@ check: validate python -m pytest python -m ruff check scripts tests python -m ruff format --check scripts tests + +site-check: + npm --prefix website run lint + npm --prefix website test + npm --prefix website audit --omit=dev --audit-level=high diff --git a/README.md b/README.md index 2590737..d88ec73 100644 --- a/README.md +++ b/README.md @@ -29,6 +29,10 @@

+

+ Open the interactive research catalog → +

+ This repository is an evidence-first catalog of papers that study **Claude Code** and **Codex CLI** as complete products—not merely Claude or GPT-family models. It records the baseline configuration, task, intervention, reported result, comparison controls, caveats, and official artifacts. > [!IMPORTANT] @@ -81,6 +85,9 @@ Excluded from the primary catalog: These papers numerically compare a proposed method with Claude Code or Codex CLI. “Direct” does not imply same-model or same-budget parity—check the controls column and linked dossier. +
+Open the raw direct-comparison table + | System / paper | Venue | Product baseline | Task | What changed | Reported evidence | Controls | |---|---|---|---|---|---|---| @@ -99,6 +106,8 @@ These papers numerically compare a proposed method with Claude Code or Codex CLI | **[MLZero](papers/mlzero-2025.md)**
[paper](https://papers.neurips.cc/paper_files/paper/2025/hash/63ed15a46a143ff57484b38cd6b85d91-Abstract-Conference.html) · [artifact](https://github.com/autogluon/autogluon-assistant) | NeurIPS 2025
main | Codex CLI (GPT-4.1 and o4-mini) | End-to-end machine learning automation | Hierarchical agents with multimodal perception, semantic and episodic memory, and a planning-coding-evaluation loop
`multi-agent` `memory` `verifier-loop` `test-feedback` | MLZero led MLE-Bench Lite with six gold medals and achieved 0.92 success on its multimodal benchmark; one appendix setting reports 6.5% errors versus 26.9% for Codex CLI. | model: unknown
budget: unknown
evidence: medium | +
+ ## What repeatedly works Across the current catalog, successful methods repeatedly add structure around the model: @@ -116,6 +125,9 @@ See the generated [method view](views/by-method.md) and [taxonomy](docs/taxonomy These papers contain useful product-level evidence, but their central numeric result is a component comparison or another agent's result rather than a clean Claude Code/Codex CLI head-to-head. +
+Open the raw related-method table + | System / paper | Venue | Product baseline | Task | What changed | Reported evidence | Controls | |---|---|---|---|---|---|---| @@ -123,10 +135,15 @@ These papers contain useful product-level evidence, but their central numeric re | **[SCATE](papers/scate-2026.md)**
[paper](https://arxiv.org/abs/2607.08983) | arXiv 2026
preprint | Claude Code | Automated test generation | Contextual-bandit supervisor that selects testing actions from current coverage and testability state
`test-feedback` `verifier-loop` | Line coverage improves 32.3% and branch coverage 30.9% over agent-only Gemini CLI; adaptation is also evaluated with Claude Code. | model: unknown
budget: unknown
evidence: contextual | +
+ ## Evaluation-only papers These papers benchmark or diagnose the products without proposing a method intended to outperform them. +
+Open the raw evaluation table + | System / paper | Venue | Product baseline | Task | What changed | Reported evidence | Controls | |---|---|---|---|---|---|---| @@ -135,16 +152,23 @@ These papers benchmark or diagnose the products without proposing a method inten | **[BountyBench](papers/bountybench-2025.md)**
[paper](https://proceedings.neurips.cc/paper_files/paper/2025/hash/faed4276b52ef762879db4142655c699-Abstract-Datasets_and_Benchmarks_Track.html) · [artifact](https://github.com/bountybench/bountybench) | NeurIPS 2025
dataset benchmark | Claude Code
Codex CLI (o3-high and o4-mini) | Vulnerability detection, exploitation, and patching | Evaluation-only benchmark of offensive and defensive cybersecurity agents
`verifier-loop` | Codex o3-high detects 12.5% and patches 90%; Claude Code patches 87.5% and exploits 57.5% in the reported settings. | model: unknown
budget: unknown
evidence: high | +
+ ## Historical OpenAI Codex model papers These entries study the pre-CLI OpenAI Codex model and are never mixed with modern Codex CLI results. +
+Open the raw historical-model table + | System / paper | Venue | Product baseline | Task | What changed | Reported evidence | Controls | |---|---|---|---|---|---|---| | **[TiCoder](papers/ticoder-2022.md)**
[paper](https://arxiv.org/abs/2208.05950) · [artifact](https://github.com/microsoft/TiCoder) | AST at ICSE 2022
workshop | OpenAI Codex model (OpenAI Codex) | Interactive function-level code generation | Generate tests to formalize user intent, collect lightweight feedback, and rank or prune candidate programs
`test-feedback` `verifier-loop` | With one to five simulated user queries, Codex pass@1 gains 22.49 to 37.71 points on MBPP and 24.79 to 53.98 points on HumanEval. | model: same
budget: different
evidence: high | +
+ ## Evidence classes - **Direct comparison** — numeric comparison with the production product. diff --git a/README.zh-CN.md b/README.zh-CN.md index 8c22ebc..4a3e06d 100644 --- a/README.zh-CN.md +++ b/README.zh-CN.md @@ -29,6 +29,10 @@

+

+ 打开可交互论文目录 → +

+ 这是一个以证据为核心的论文库，研究对象是完整的 **Claude Code** 与 **Codex CLI** 产品，而不只是 Claude 或 GPT 系列模型。每篇论文都记录 baseline 配置、任务、新增方法、论文结果、实验控制、风险说明和官方 artifact。 > [!IMPORTANT] @@ -81,6 +85,9 @@ 这些论文把提出的方法与 Claude Code 或 Codex CLI 做了数值比较。“直接”不代表模型和预算相同，请同时查看可比性字段和论文证据页。 +
+展开原始直接对比表 + | 系统 / 论文 | 会议 | 产品 baseline | 任务 | 新增方法 | 论文结果 | 可比性 | |---|---|---|---|---|---|---| @@ -99,6 +106,8 @@ | **[MLZero](papers/mlzero-2025.md)**
[paper](https://papers.neurips.cc/paper_files/paper/2025/hash/63ed15a46a143ff57484b38cd6b85d91-Abstract-Conference.html) · [artifact](https://github.com/autogluon/autogluon-assistant) | NeurIPS 2025
main | Codex CLI (GPT-4.1 and o4-mini) | End-to-end machine learning automation | Hierarchical agents with multimodal perception, semantic and episodic memory, and a planning-coding-evaluation loop
`multi-agent` `memory` `verifier-loop` `test-feedback` | MLZero led MLE-Bench Lite with six gold medals and achieved 0.92 success on its multimodal benchmark; one appendix setting reports 6.5% errors versus 26.9% for Codex CLI. | model: unknown
budget: unknown
evidence: medium | +
+ ## 反复出现的有效方法 1. **持久化仓库状态**：把计划、架构、依赖和设计知识放到上下文窗口之外。 @@ -114,6 +123,9 @@ 这些论文包含有用的产品证据，但主要数值可能来自组件实验或其他 agent，不构成严格的 Claude Code/Codex CLI 正面对比。 +
+展开原始相关方法表 + | 系统 / 论文 | 会议 | 产品 baseline | 任务 | 新增方法 | 论文结果 | 可比性 | |---|---|---|---|---|---|---| @@ -121,10 +133,15 @@ | **[SCATE](papers/scate-2026.md)**
[paper](https://arxiv.org/abs/2607.08983) | arXiv 2026
preprint | Claude Code | Automated test generation | Contextual-bandit supervisor that selects testing actions from current coverage and testability state
`test-feedback` `verifier-loop` | Line coverage improves 32.3% and branch coverage 30.9% over agent-only Gemini CLI; adaptation is also evaluated with Claude Code. | model: unknown
budget: unknown
evidence: contextual | +
+ ## 仅评测论文 这些论文负责 benchmark、测量或故障分析，没有提出专门超越产品的新方法。 +
+展开原始评测论文表 + | 系统 / 论文 | 会议 | 产品 baseline | 任务 | 新增方法 | 论文结果 | 可比性 | |---|---|---|---|---|---|---| @@ -133,16 +150,23 @@ | **[BountyBench](papers/bountybench-2025.md)**
[paper](https://proceedings.neurips.cc/paper_files/paper/2025/hash/faed4276b52ef762879db4142655c699-Abstract-Datasets_and_Benchmarks_Track.html) · [artifact](https://github.com/bountybench/bountybench) | NeurIPS 2025
dataset benchmark | Claude Code
Codex CLI (o3-high and o4-mini) | Vulnerability detection, exploitation, and patching | Evaluation-only benchmark of offensive and defensive cybersecurity agents
`verifier-loop` | Codex o3-high detects 12.5% and patches 90%; Claude Code patches 87.5% and exploits 57.5% in the reported settings. | model: unknown
budget: unknown
evidence: high | +
+ ## 旧 OpenAI Codex 模型论文 这些论文研究的是 Codex CLI 出现前的 OpenAI Codex 模型，不与现代 Codex CLI 结果混合。 +
+展开原始历史模型表 + | 系统 / 论文 | 会议 | 产品 baseline | 任务 | 新增方法 | 论文结果 | 可比性 | |---|---|---|---|---|---|---| | **[TiCoder](papers/ticoder-2022.md)**
[paper](https://arxiv.org/abs/2208.05950) · [artifact](https://github.com/microsoft/TiCoder) | AST at ICSE 2022
workshop | OpenAI Codex model (OpenAI Codex) | Interactive function-level code generation | Generate tests to formalize user intent, collect lightweight feedback, and rank or prune candidate programs
`test-feedback` `verifier-loop` | With one to five simulated user queries, Codex pass@1 gains 22.49 to 37.71 points on MBPP and 24.79 to 53.98 points on HumanEval. | model: same
budget: different
evidence: high | +
+ ## 数据与自动校验 `data/papers.yaml` 是唯一数据源。构建流程会校验 Schema、生成中英文 README、导出 JSON、生成每篇论文的证据页和研究视图，并检查内部链接、执行测试与 lint： diff --git a/ROADMAP.md b/ROADMAP.md index 9910b83..f76cadc 100644 --- a/ROADMAP.md +++ b/ROADMAP.md @@ -13,6 +13,8 @@ The catalog optimizes for evidence quality before paper count. - [x] English and Simplified Chinese entry points - [x] Schema, tests, linting, and CI - [x] Structured paper-suggestion workflow +- [x] Interactive bilingual site generated from the same catalog +- [x] Matched-model and matched-budget comparison filters ## v0.2 — Evidence depth @@ -45,7 +47,5 @@ Model-only papers remain out of scope unless they study a product harness direct ## Long-term -- Interactive static site generated from the same catalog -- Comparison matrices with matched-model and matched-budget filters - Reproduction packs for a small set of high-impact claims - Community-maintained venue watchlist and artifact-status audits diff --git a/scripts/build_readme.py b/scripts/build_readme.py index 8ccf92d..45a66f4 100644 --- a/scripts/build_readme.py +++ b/scripts/build_readme.py @@ -519,10 +519,12 @@ def render_by_venue(catalog: dict) -> str: def render_all() -> dict[Path, str]: catalog = load_catalog() + catalog_json = json.dumps(catalog, indent=2, ensure_ascii=False) + "\n" outputs = { README_PATH: render_marked_readme(README_PATH, catalog, "en"), README_ZH_PATH: render_marked_readme(README_ZH_PATH, catalog, "zh"), - ROOT / "data" / "papers.json": json.dumps(catalog, indent=2, ensure_ascii=False) + "\n", + ROOT / "data" / "papers.json": catalog_json, + ROOT / "website" / "data" / "catalog.json": catalog_json, ROOT / "papers" / "README.md": render_paper_index(catalog), ROOT / "views" / "README.md": render_views_index(), ROOT / "views" / "by-product.md": render_by_product(catalog), diff --git a/scripts/check_links.py b/scripts/check_links.py index 4b87593..9a6949c 100644 --- a/scripts/check_links.py +++ b/scripts/check_links.py @@ -11,7 +11,17 @@ ROOT = Path(__file__).resolve().parents[1] MARKDOWN_LINK = re.compile(r"\[[^\]]*\]\(([^)]+)\)") HTML_LINK = re.compile(r'(?:href|src)="([^"]+)"') -EXCLUDED_PARTS = {".git", ".venv"} +EXCLUDED_PARTS = { + ".git", + ".next", + ".venv", + ".vinext", + ".wrangler", + "coverage", + "dist", + "node_modules", + "out", +} def markdown_files() -> list[Path]: diff --git a/tests/test_catalog.py b/tests/test_catalog.py index 980f4d3..70c1b6e 100644 --- a/tests/test_catalog.py +++ b/tests/test_catalog.py @@ -5,6 +5,7 @@ from pathlib import Path from xml.etree import ElementTree +from scripts import check_links from scripts.discover_candidates import parse_feed ROOT = Path(__file__).resolve().parents[1] @@ -30,6 +31,18 @@ def test_generated_readme_is_current() -> None: assert result.returncode == 0, result.stderr +def test_link_scan_excludes_dependencies_and_build_outputs(tmp_path: Path, monkeypatch) -> None: + (tmp_path / "README.md").write_text("# Project\n", encoding="utf-8") + for directory in ("node_modules", "dist", ".next", ".wrangler"): + path = tmp_path / directory + path.mkdir() + (path / "README.md").write_text("[missing](missing.md)\n", encoding="utf-8") + + monkeypatch.setattr(check_links, "ROOT", tmp_path) + + assert check_links.markdown_files() == [tmp_path / "README.md"] + + def test_arxiv_feed_parser_strips_version_and_normalizes_text() -> None: feed = ElementTree.fromstring( """ diff --git a/website/.gitignore b/website/.gitignore new file mode 100644 index 0000000..967037f --- /dev/null +++ b/website/.gitignore @@ -0,0 +1,40 @@ +# See https://help.github.com/articles/ignoring-files/ for more about ignoring files. + +# dependencies +/node_modules +/.pnp +.pnp.* +.yarn/* +!.yarn/patches +!.yarn/plugins +!.yarn/releases +!.yarn/versions + +# testing +/coverage + +# next.js +/.next/ +/.vinext/ +/out/ + +# misc +.DS_Store +*.pem + +# debug +npm-debug.log* +yarn-debug.log* +yarn-error.log* +.pnpm-debug.log* + +# env files (can opt-in for committing if needed) +.env* + +# vercel +.vercel + +/dist/ +/.wrangler/ +/outputs/ +/work/ diff --git a/website/.openai/hosting.json b/website/.openai/hosting.json new file mode 100644 index 0000000..b681747 --- /dev/null +++ b/website/.openai/hosting.json @@ -0,0 +1,5 @@ +{ + "project_id": "appgprj_6a880c0383448191a8e115732079a231", + "d1": null, + "r2": null +} diff --git a/website/README.md b/website/README.md new file mode 100644 index 0000000..0bb3504 --- /dev/null +++ b/website/README.md @@ -0,0 +1,10 @@ +# Research catalog website + +Interactive HTML front end for the evidence catalog in `../data/papers.yaml`. + +The site provides full-text search, product and evidence filters, method views, +comparison-control summaries, expandable paper dossiers, English/Chinese UI, +and a small GitHub Star call to action. + +`../scripts/build_readme.py` generates `data/catalog.json`; do not edit that +file by hand. diff --git a/website/app/CatalogExplorer.tsx b/website/app/CatalogExplorer.tsx new file mode 100644 index 0000000..7216dca --- /dev/null +++ b/website/app/CatalogExplorer.tsx @@ -0,0 +1,812 @@ +"use client"; + +import { useEffect, useMemo, useRef, useState } from "react"; + +type ProductId = "claude-code" | "codex-cli" | "openai-codex-model"; +type Classification = "direct" | "related" | "evaluation" | "historical"; +type Language = "en" | "zh"; +type FairnessFilter = "all" | "controlled" | "unknown" | "mismatch"; + +export type Paper = { + id: string; + title: string; + authors: string[]; + year: number; + venue: string; + publication_status: string; + classification: Classification; + system: string; + paper_url: string; + artifact_url?: string; + artifact_status: "official" | "community" | "not-found"; + arxiv_id?: string; + doi?: string; + published_at?: string; + products: Array<{ + product: ProductId; + role: string; + model: string; + version: string; + }>; + task: { summary: string; benchmark: string }; + method: { summary: string; tags: string[] }; + evidence: { + result: string; + strength: "high" | "medium" | "contextual"; + same_model: "yes" | "no" | "unknown"; + same_budget: "yes" | "no" | "unknown"; + claim_type: string; + comparison_scope: string; + source_location: string; + caveats: string; + }; +}; + +const REPOSITORY_URL = + "https://github.com/MicroMilo/awesome-claude-code-codex-papers"; + +const PRODUCT_LABELS: Record = { + "claude-code": "Claude Code", + "codex-cli": "Codex CLI", + "openai-codex-model": "Codex model", +}; + +const copy = { + en: { + papers: "Papers", + methods: "Patterns", + fairness: "Fairness", + star: "Star on GitHub ↗", + eyebrow: "Evidence, not leaderboard hype", + heroLead: "What actually beats", + heroAccent: "Claude Code & Codex?", + heroDeck: + "A readable research index for the methods, controls, and caveats behind production coding-agent comparisons.", + explore: "Explore the evidence ↓", + reviewed: "Last reviewed", + reviewedPapers: "reviewed papers", + directComparisons: "direct comparisons", + officialArtifacts: "official artifacts", + productionAgents: "production agents", + catalogEyebrow: "Research catalog", + catalogTitle: "Start with the result. Open the controls only when needed.", + search: "Search systems, tasks, methods…", + product: "Product", + evidenceClass: "Evidence class", + comparison: "Comparison", + venue: "Venue", + method: "Method", + all: "All", + direct: "Direct", + related: "Related", + evaluation: "Evaluation", + historical: "Historical", + controlled: "Same model + budget", + unknown: "Controls unclear", + mismatch: "Known mismatch", + clear: "Clear filters", + results: "matching papers", + noResults: "No paper matches these filters.", + reset: "Reset the catalog", + inspect: "Inspect evidence", + paper: "Paper ↗", + artifact: "Artifact ↗", + methodPattern: "Recurring method patterns", + methodTitle: "Structure around the model keeps winning.", + methodDeck: + "Select a pattern to see the papers behind it. Counts are generated from the same reviewed catalog.", + fairnessEyebrow: "Comparison sanity check", + fairnessTitle: "A direct comparison is not automatically a fair comparison.", + fairControlled: "Controlled", + fairUnknown: "Unclear", + fairMismatch: "Mismatch", + fairControlledText: "The paper explicitly holds model and budget fixed.", + fairUnknownText: "At least one important control is not reported clearly.", + fairMismatchText: "The paper explicitly changes the model or budget.", + task: "Task", + benchmark: "Benchmark / scale", + intervention: "What changed", + reportedEvidence: "Reported evidence", + controls: "Comparison controls", + sameModel: "Same model", + sameBudget: "Same budget", + strength: "Evidence strength", + source: "Where to verify", + caveat: "Read this caveat", + productConfig: "Product configuration", + model: "Model", + version: "Version", + notReported: "Not reported", + close: "Close", + footerLead: "Did this save you a paper-reading session?", + footerCopy: + "A star helps more researchers find the evidence—and tells us to keep auditing it.", + footerButton: "Star the repository ★", + footerNote: "Open data · primary sources · explicit caveats", + }, + zh: { + papers: "论文", + methods: "方法", + fairness: "公平性", + star: "去 GitHub 点 Star ↗", + eyebrow: "看证据，不看榜单气氛", + heroLead: "到底什么方法能超越", + heroAccent: "Claude Code 与 Codex？", + heroDeck: + "把工业 coding agent 论文里的方法、实验控制和限制条件，整理成真正读得下去的研究索引。", + explore: "开始看证据 ↓", + reviewed: "最近审计", + reviewedPapers: "篇已审论文", + directComparisons: "篇直接对比", + officialArtifacts: "个官方 Artifact", + productionAgents: "个工业 Agent", + catalogEyebrow: "论文目录", + catalogTitle: "先看结果；需要时，再展开实验控制和限制。", + search: "搜索系统、任务或方法…", + product: "产品", + evidenceClass: "证据类型", + comparison: "实验控制", + venue: "会议", + method: "方法", + all: "全部", + direct: "直接对比", + related: "相关方法", + evaluation: "仅评测", + historical: "历史模型", + controlled: "相同模型与预算", + unknown: "控制不明确", + mismatch: "已知不一致", + clear: "清空筛选", + results: "篇匹配论文", + noResults: "没有论文符合当前筛选。", + reset: "重置目录", + inspect: "查看证据", + paper: "打开论文 ↗", + artifact: "打开 Artifact ↗", + methodPattern: "反复出现的方法", + methodTitle: "真正有效的，往往是模型周围的结构。", + methodDeck: "点击方法即可筛选对应论文；数量直接来自审计后的目录。", + fairnessEyebrow: "先检查可比性", + fairnessTitle: "有直接对比，不等于做了公平对比。", + fairControlled: "严格控制", + fairUnknown: "信息不明", + fairMismatch: "条件不同", + fairControlledText: "论文明确保持模型和预算一致。", + fairUnknownText: "至少一个关键实验控制没有写清楚。", + fairMismatchText: "论文明确使用了不同模型或预算。", + task: "任务", + benchmark: "Benchmark / 规模", + intervention: "新增了什么", + reportedEvidence: "论文报告的结果", + controls: "实验控制", + sameModel: "模型相同", + sameBudget: "预算相同", + strength: "证据强度", + source: "证据位置", + caveat: "需要注意", + productConfig: "产品配置", + model: "模型", + version: "版本", + notReported: "未报告", + close: "关闭", + footerLead: "这个目录帮你省下了一轮翻论文的时间吗？", + footerCopy: "点一个 Star，让更多研究者找到这些证据，也让我们知道值得继续审计。", + footerButton: "去仓库点个 Star ★", + footerNote: "开放数据 · 一手来源 · 明确限制", + }, +}; + +const CLASS_LABELS: Record> = { + en: { + direct: "Direct comparison", + related: "Related method", + evaluation: "Evaluation", + historical: "Historical", + }, + zh: { + direct: "直接对比", + related: "相关方法", + evaluation: "仅评测", + historical: "历史模型", + }, +}; + +function fairnessGroup(paper: Paper): Exclude { + if ( + paper.evidence.same_model === "yes" && + paper.evidence.same_budget === "yes" + ) { + return "controlled"; + } + if ( + paper.evidence.same_model === "no" || + paper.evidence.same_budget === "no" + ) { + return "mismatch"; + } + return "unknown"; +} + +function readableValue(value: string, fallback: string) { + return value === "not-reported" || value === "not-applicable" + ? fallback + : value; +} + +type Props = { papers: Paper[]; reviewedAt: string }; + +export function CatalogExplorer({ papers, reviewedAt }: Props) { + const [language, setLanguage] = useState("en"); + const [query, setQuery] = useState(""); + const [product, setProduct] = useState<"all" | ProductId>("all"); + const [classification, setClassification] = useState< + "all" | Classification + >("all"); + const [fairness, setFairness] = useState("all"); + const [venue, setVenue] = useState("all"); + const [method, setMethod] = useState("all"); + const [activePaper, setActivePaper] = useState(null); + const dialogCloseButton = useRef(null); + + const t = copy[language]; + const directCount = papers.filter( + (paper) => paper.classification === "direct", + ).length; + const artifactCount = papers.filter( + (paper) => paper.artifact_status === "official", + ).length; + + const venues = useMemo( + () => [...new Set(papers.map((paper) => paper.venue))].sort(), + [papers], + ); + + const methodCounts = useMemo(() => { + const counts = new Map(); + papers.forEach((paper) => { + paper.method.tags.forEach((tag) => { + counts.set(tag, (counts.get(tag) ?? 0) + 1); + }); + }); + return [...counts.entries()].sort( + ([tagA, countA], [tagB, countB]) => + countB - countA || tagA.localeCompare(tagB), + ); + }, [papers]); + + const fairnessCounts = useMemo( + () => ({ + controlled: papers.filter((paper) => fairnessGroup(paper) === "controlled") + .length, + unknown: papers.filter((paper) => fairnessGroup(paper) === "unknown") + .length, + mismatch: papers.filter((paper) => fairnessGroup(paper) === "mismatch") + .length, + }), + [papers], + ); + + const filtered = useMemo(() => { + const needle = query.trim().toLowerCase(); + const rank: Record = { + direct: 0, + evaluation: 1, + related: 2, + historical: 3, + }; + return papers + .filter((paper) => { + const matchesQuery = + !needle || + [ + paper.system, + paper.title, + paper.venue, + paper.task.summary, + paper.task.benchmark, + paper.method.summary, + paper.evidence.result, + ...paper.authors, + ...paper.method.tags, + ] + .join(" ") + .toLowerCase() + .includes(needle); + const matchesProduct = + product === "all" || + paper.products.some((item) => item.product === product); + const matchesClass = + classification === "all" || paper.classification === classification; + const matchesFairness = + fairness === "all" || fairnessGroup(paper) === fairness; + const matchesVenue = venue === "all" || paper.venue === venue; + const matchesMethod = + method === "all" || paper.method.tags.includes(method); + return ( + matchesQuery && + matchesProduct && + matchesClass && + matchesFairness && + matchesVenue && + matchesMethod + ); + }) + .sort( + (paperA, paperB) => + rank[paperA.classification] - rank[paperB.classification] || + paperB.year - paperA.year || + paperA.system.localeCompare(paperB.system), + ); + }, [classification, fairness, method, papers, product, query, venue]); + + const filtersActive = + query !== "" || + product !== "all" || + classification !== "all" || + fairness !== "all" || + venue !== "all" || + method !== "all"; + + useEffect(() => { + document.documentElement.lang = language === "zh" ? "zh-CN" : "en"; + }, [language]); + + useEffect(() => { + if (!activePaper) return; + const previousOverflow = document.body.style.overflow; + document.body.style.overflow = "hidden"; + dialogCloseButton.current?.focus(); + const closeOnEscape = (event: KeyboardEvent) => { + if (event.key === "Escape") setActivePaper(null); + }; + window.addEventListener("keydown", closeOnEscape); + return () => { + document.body.style.overflow = previousOverflow; + window.removeEventListener("keydown", closeOnEscape); + }; + }, [activePaper]); + + const clearFilters = () => { + setQuery(""); + setProduct("all"); + setClassification("all"); + setFairness("all"); + setVenue("all"); + setMethod("all"); + }; + + const chooseMethod = (tag: string) => { + setMethod(tag); + document.getElementById("catalog")?.scrollIntoView({ behavior: "smooth" }); + }; + + const chooseFairness = (value: Exclude) => { + setFairness(value); + document.getElementById("catalog")?.scrollIntoView({ behavior: "smooth" }); + }; + + const toggleLanguage = () => { + setLanguage((current) => (current === "en" ? "zh" : "en")); + }; + + return ( +
+
+ + >_ + Agent Papers + + +
+ +
+
+

{t.eyebrow}

+

+ {t.heroLead} + {t.heroAccent} +

+

{t.heroDeck}

+
+ + {t.explore} + + + {t.reviewed} {reviewedAt} + +
+
+ +
+
+ >_ + Claude Code +
+
+ >_ + Codex CLI +
+ +
+ ✓ + method + budget + result +
+
+
+ +
+
+ {papers.length} + {t.reviewedPapers} +
+
+ {directCount} + {t.directComparisons} +
+
+ {artifactCount} + {t.officialArtifacts} +
+
+ 2 + {t.productionAgents} +
+
+ +
+
+
+

{t.catalogEyebrow}

+

{t.catalogTitle}

+
+ +
+ +
+
+ {t.product} +
+ {[ + ["all", t.all], + ["claude-code", "Claude Code"], + ["codex-cli", "Codex CLI"], + ].map(([value, label]) => ( + + ))} +
+
+ + + + + + + + +
+ +
+ + {filtered.length} {t.results} + + {filtersActive && ( + + )} +
+ + {filtered.length > 0 ? ( +
+ {filtered.map((paper) => ( +
+
+ + {CLASS_LABELS[language][paper.classification]} + + + {paper.venue} · {paper.year} + +
+

{paper.system}

+

{paper.title}

+
+ {paper.products.map((item) => ( + {PRODUCT_LABELS[item.product]} + ))} +
+
+ {t.intervention} +

{paper.method.summary}

+
+
{paper.evidence.result}
+
+ + M · {paper.evidence.same_model} + + + B · {paper.evidence.same_budget} + + + E · {paper.evidence.strength} + +
+
+ {paper.method.tags.slice(0, 2).join(" · ")} + +
+
+ ))} +
+ ) : ( +
+ 0 +

{t.noResults}

+ +
+ )} +
+ +
+
+
+

{t.methodPattern}

+

{t.methodTitle}

+
+

{t.methodDeck}

+
+
+ {methodCounts.slice(0, 12).map(([tag, count], index) => ( + + ))} +
+
+ +
+
+

{t.fairnessEyebrow}

+

{t.fairnessTitle}

+
+
+ + + +
+
+ + + + {activePaper && ( +
{ + if (event.target === event.currentTarget) setActivePaper(null); + }} + > +
+ +
+ + {CLASS_LABELS[language][activePaper.classification]} + +

+ {activePaper.venue} · {activePaper.year} · {activePaper.publication_status} +

+

{activePaper.system}

+

{activePaper.title}

+

{activePaper.authors.join(", ")}

+
+ +
+

{t.productConfig}

+ {activePaper.products.map((item) => ( +
+ {PRODUCT_LABELS[item.product]} + + {t.model}: {readableValue(item.model, t.notReported)} + + + {t.version}: {readableValue(item.version, t.notReported)} + +
+ ))} +
+ +
+
+

{t.task}

+

{activePaper.task.summary}

+ + {t.benchmark}: {activePaper.task.benchmark} + +
+
+

{t.intervention}

+

{activePaper.method.summary}

+
+ {activePaper.method.tags.map((tag) => ( + {tag} + ))} +
+
+
+ +
+

{t.reportedEvidence}

+
{activePaper.evidence.result}
+
+ +
+

{t.controls}

+
+
+ {t.sameModel} + {activePaper.evidence.same_model} +
+
+ {t.sameBudget} + {activePaper.evidence.same_budget} +
+
+ {t.strength} + {activePaper.evidence.strength} +
+
+
+ +
+
+

{t.source}

+

{activePaper.evidence.source_location}

+
+
+

{t.caveat}

+

{activePaper.evidence.caveats}

+
+
+ +
+ + {t.paper} + + {activePaper.artifact_url && ( + + {t.artifact} + + )} +
+
+
+ )} +
+ ); +} diff --git a/website/app/globals.css b/website/app/globals.css new file mode 100644 index 0000000..124db4c --- /dev/null +++ b/website/app/globals.css @@ -0,0 +1,1298 @@ +@import "tailwindcss"; + +:root { + --ink: #0d1718; + --ink-soft: #334445; + --paper: #f1eee5; + --paper-bright: #fbf9f3; + --line: rgba(13, 23, 24, 0.17); + --coral: #f16f51; + --cyan: #4bcbd5; + --mint: #7be0a9; +} + +* { + box-sizing: border-box; +} + +html { + scroll-behavior: smooth; +} + +body { + margin: 0; + background: + linear-gradient(rgba(13, 23, 24, 0.025) 1px, transparent 1px), + linear-gradient(90deg, rgba(13, 23, 24, 0.025) 1px, transparent 1px), + var(--paper); + background-size: 32px 32px; + color: var(--ink); + font-family: var(--font-geist-sans), Arial, sans-serif; +} + +a { + color: inherit; + text-decoration: none; +} + +.site-header { + align-items: center; + backdrop-filter: blur(18px); + background: rgba(241, 238, 229, 0.86); + border-bottom: 1px solid var(--line); + display: flex; + height: 68px; + justify-content: space-between; + left: 0; + padding: 0 clamp(24px, 5vw, 80px); + position: sticky; + right: 0; + top: 0; + z-index: 20; +} + +.brand, +.site-header nav, +.hero-actions, +.card-topline, +.card-footer, +.product-list, +footer, +footer > div { + align-items: center; + display: flex; +} + +.brand { + font-family: var(--font-geist-mono), monospace; + font-size: 14px; + font-weight: 700; + gap: 10px; + letter-spacing: -0.02em; + text-transform: uppercase; +} + +.brand-mark { + color: var(--coral); + font-family: var(--font-geist-mono), monospace; + font-weight: 800; +} + +.site-header nav { + font-size: 13px; + gap: 28px; +} + +.star-link { + border: 1px solid var(--ink); + padding: 10px 15px; +} + +.hero { + display: grid; + gap: clamp(40px, 7vw, 120px); + grid-template-columns: minmax(0, 1.12fr) minmax(330px, 0.88fr); + margin: 0 auto; + max-width: 1440px; + min-height: 640px; + padding: clamp(80px, 10vw, 150px) clamp(24px, 6vw, 92px) 80px; +} + +.hero-copy { + align-self: center; +} + +.eyebrow { + color: #536567; + font-family: var(--font-geist-mono), monospace; + font-size: 11px; + font-weight: 700; + letter-spacing: 0.12em; + margin: 0 0 20px; + text-transform: uppercase; +} + +h1, +h2, +h3, +p { + margin-top: 0; +} + +h1 { + font-family: Georgia, "Times New Roman", serif; + font-size: clamp(56px, 7.3vw, 108px); + font-weight: 400; + letter-spacing: -0.075em; + line-height: 0.88; + margin-bottom: 34px; + max-width: 900px; +} + +h1 span { + color: var(--coral); + display: block; + font-style: italic; +} + +.hero-deck { + color: var(--ink-soft); + font-size: clamp(18px, 2vw, 23px); + line-height: 1.55; + max-width: 690px; +} + +.hero-actions { + gap: 24px; + margin-top: 40px; +} + +.hero-actions > span { + color: #667778; + font-family: var(--font-geist-mono), monospace; + font-size: 11px; +} + +.primary-action { + background: var(--ink); + color: var(--paper-bright); + font-size: 14px; + padding: 16px 20px; +} + +.signal-map { + align-self: center; + background: var(--ink); + border-radius: 2px; + box-shadow: 20px 20px 0 rgba(13, 23, 24, 0.09); + color: white; + display: grid; + gap: 16px; + grid-template-columns: 1fr 64px 1.18fr; + min-height: 380px; + overflow: hidden; + padding: 44px; + position: relative; +} + +.signal-map::before { + background: radial-gradient(circle, rgba(75, 203, 213, 0.22), transparent 68%); + content: ""; + height: 360px; + position: absolute; + right: -120px; + top: -120px; + width: 360px; +} + +.signal-source { + align-self: center; + border: 1px solid rgba(255, 255, 255, 0.26); + display: flex; + flex-direction: column; + gap: 12px; + grid-column: 1; + padding: 18px; +} + +.signal-source span { + font-family: var(--font-geist-mono), monospace; + font-size: 22px; +} + +.signal-source small { + color: rgba(255, 255, 255, 0.64); +} + +.signal-source.coral { + border-left: 3px solid var(--coral); +} + +.signal-source.cyan { + border-left: 3px solid var(--cyan); +} + +.signal-lines { + align-self: center; + display: flex; + flex-direction: column; + gap: 26px; + grid-column: 2; + grid-row: 1 / 3; +} + +.signal-lines i { + background: linear-gradient(90deg, var(--coral), var(--mint)); + display: block; + height: 1px; + position: relative; +} + +.signal-lines i::after { + background: var(--mint); + content: ""; + height: 5px; + position: absolute; + right: 0; + top: -2px; + width: 5px; +} + +.signal-proof { + align-self: center; + border: 1px solid rgba(123, 224, 169, 0.5); + display: grid; + gap: 14px; + grid-column: 3; + grid-row: 1 / 3; + padding: 26px; +} + +.signal-proof strong { + color: var(--mint); + font-size: 48px; + line-height: 1; +} + +.signal-proof span { + border-top: 1px solid rgba(255, 255, 255, 0.13); + color: rgba(255, 255, 255, 0.65); + font-family: var(--font-geist-mono), monospace; + font-size: 10px; + padding-top: 10px; + text-transform: uppercase; +} + +.stats { + border-bottom: 1px solid var(--line); + border-top: 1px solid var(--line); + display: grid; + grid-template-columns: repeat(4, 1fr); +} + +.stats > div { + border-right: 1px solid var(--line); + padding: 32px clamp(24px, 5vw, 72px); +} + +.stats > div:last-child { + border-right: 0; +} + +.stats strong { + display: block; + font-family: Georgia, "Times New Roman", serif; + font-size: 48px; + font-weight: 400; +} + +.stats span { + color: #627172; + font-size: 12px; +} + +.catalog-section { + margin: 0 auto; + max-width: 1440px; + padding: 120px clamp(24px, 6vw, 92px); +} + +.section-heading { + align-items: end; + display: flex; + gap: 40px; + justify-content: space-between; +} + +.section-heading h2, +.method-note h2 { + font-family: Georgia, "Times New Roman", serif; + font-size: clamp(36px, 4.5vw, 62px); + font-weight: 400; + letter-spacing: -0.05em; + line-height: 1; + margin-bottom: 0; + max-width: 740px; +} + +.search-box { + align-items: center; + border-bottom: 1px solid var(--ink); + display: flex; + flex: 0 1 380px; + gap: 10px; + padding: 12px 0; +} + +.search-box span { + font-size: 24px; +} + +.search-box input { + background: transparent; + border: 0; + color: var(--ink); + font: inherit; + outline: 0; + width: 100%; +} + +.result-line { + color: #627172; + display: flex; + font-family: var(--font-geist-mono), monospace; + font-size: 11px; + justify-content: space-between; + margin: 64px 0 20px; + text-transform: uppercase; +} + +.paper-grid { + display: grid; + gap: 1px; + grid-template-columns: repeat(3, 1fr); +} + +.paper-card { + background: var(--paper-bright); + border: 1px solid var(--line); + display: flex; + flex-direction: column; + margin: 0 -1px -1px 0; + min-height: 430px; + padding: 28px; + transition: transform 180ms ease, box-shadow 180ms ease; +} + +.paper-card:hover { + box-shadow: 8px 8px 0 rgba(13, 23, 24, 0.12); + transform: translate(-4px, -4px); + z-index: 2; +} + +.card-topline, +.card-footer { + color: #657576; + font-family: var(--font-geist-mono), monospace; + font-size: 10px; + justify-content: space-between; + text-transform: uppercase; +} + +.class-pill { + border: 1px solid var(--line); + padding: 7px 9px; +} + +.class-pill.direct { + background: rgba(241, 111, 81, 0.12); + border-color: rgba(241, 111, 81, 0.45); +} + +.class-pill.evaluation { + background: rgba(75, 203, 213, 0.12); +} + +.paper-card h3 { + font-family: Georgia, "Times New Roman", serif; + font-size: 34px; + font-weight: 400; + letter-spacing: -0.04em; + margin: 34px 0 8px; +} + +.paper-title { + color: #536364; + font-size: 13px; + line-height: 1.45; + min-height: 58px; +} + +.product-list { + flex-wrap: wrap; + gap: 8px; + margin: 14px 0 24px; +} + +.product-list span { + background: var(--ink); + color: white; + font-size: 10px; + padding: 7px 9px; +} + +.result-copy { + font-size: 14px; + line-height: 1.62; +} + +.card-footer { + border-top: 1px solid var(--line); + margin-top: auto; + padding-top: 18px; +} + +.card-footer a { + color: #bd492e; + font-size: 11px; + font-weight: 700; +} + +.method-note { + background: var(--ink); + color: var(--paper-bright); + padding: 100px clamp(24px, 10vw, 160px); +} + +.method-note .eyebrow { + color: var(--mint); +} + +.method-note p:last-child { + color: rgba(255, 255, 255, 0.65); + font-size: 18px; + line-height: 1.7; + margin: 32px 0 0; + max-width: 760px; +} + +footer { + background: #071011; + color: white; + justify-content: space-between; + padding: 42px clamp(24px, 6vw, 92px); +} + +footer > div { + gap: 14px; +} + +footer p { + color: rgba(255, 255, 255, 0.55); + font-size: 12px; + margin: 0; +} + +footer > a { + border-bottom: 1px solid var(--coral); + color: var(--coral); + font-family: var(--font-geist-mono), monospace; + font-size: 12px; + padding-bottom: 6px; +} + +@media (max-width: 980px) { + .hero { + grid-template-columns: 1fr; + } + + .signal-map { + min-height: 320px; + } + + .paper-grid { + grid-template-columns: repeat(2, 1fr); + } + + .section-heading { + align-items: stretch; + flex-direction: column; + } + + .search-box { + flex-basis: auto; + max-width: 500px; + } +} + +@media (max-width: 680px) { + .site-header nav > a:not(.star-link) { + display: none; + } + + .hero { + min-height: auto; + padding-top: 80px; + } + + h1 { + font-size: clamp(48px, 15vw, 72px); + } + + .signal-map { + grid-template-columns: 1fr; + padding: 28px; + } + + .signal-source, + .signal-proof, + .signal-lines { + grid-column: 1; + grid-row: auto; + } + + .signal-lines { + display: none; + } + + .stats { + grid-template-columns: repeat(2, 1fr); + } + + .stats > div:nth-child(2) { + border-right: 0; + } + + .paper-grid { + grid-template-columns: 1fr; + } + + .result-line span:last-child { + display: none; + } + + footer { + align-items: flex-start; + flex-direction: column; + gap: 28px; + } +} + +@media (prefers-reduced-motion: reduce) { + html { + scroll-behavior: auto; + } + + .paper-card { + transition: none; + } +} + +button, +input, +select { + font: inherit; +} + +button { + color: inherit; +} + +button, +select { + cursor: pointer; +} + +:focus-visible { + outline: 3px solid var(--cyan); + outline-offset: 3px; +} + +.sr-only { + height: 1px; + margin: -1px; + overflow: hidden; + padding: 0; + position: absolute; + width: 1px; + clip: rect(0, 0, 0, 0); + white-space: nowrap; +} + +.language-toggle { + background: transparent; + border: 0; + color: #536567; + font-family: var(--font-geist-mono), monospace; + font-size: 11px; + padding: 8px 0; +} + +.filters { + align-items: end; + border-bottom: 1px solid var(--line); + border-top: 1px solid var(--line); + display: grid; + gap: 20px; + grid-template-columns: minmax(300px, 1.5fr) repeat(4, minmax(130px, 0.7fr)); + margin-top: 72px; + padding: 22px 0; +} + +.filters fieldset, +.filters label { + border: 0; + display: flex; + flex-direction: column; + gap: 9px; + margin: 0; + min-width: 0; + padding: 0; +} + +.filters legend, +.filters label > span { + color: #657576; + font-family: var(--font-geist-mono), monospace; + font-size: 9px; + font-weight: 700; + letter-spacing: 0.08em; + text-transform: uppercase; +} + +.filters select { + appearance: none; + background: + linear-gradient(45deg, transparent 50%, var(--ink) 50%) calc(100% - 12px) + calc(50% - 2px) / 5px 5px no-repeat, + linear-gradient(135deg, var(--ink) 50%, transparent 50%) calc(100% - 7px) + calc(50% - 2px) / 5px 5px no-repeat, + transparent; + border: 0; + border-bottom: 1px solid var(--line); + border-radius: 0; + color: var(--ink); + font-size: 12px; + min-width: 0; + padding: 10px 22px 10px 0; + width: 100%; +} + +.segmented-control { + display: flex; + gap: 1px; +} + +.segmented-control button { + background: rgba(255, 255, 255, 0.42); + border: 1px solid var(--line); + font-size: 11px; + padding: 10px 12px; +} + +.segmented-control button.active { + background: var(--ink); + color: white; +} + +.result-line { + align-items: center; + margin-top: 32px; +} + +.result-line button { + background: transparent; + border: 0; + color: #bd492e; + font-family: var(--font-geist-mono), monospace; + font-size: 10px; + text-transform: uppercase; +} + +.paper-card { + min-height: 590px; +} + +.paper-card blockquote { + border-left: 3px solid var(--coral); + color: var(--ink); + font-family: Georgia, "Times New Roman", serif; + font-size: 17px; + line-height: 1.45; + margin: 0 0 22px; + padding-left: 16px; +} + +.method-summary > span { + color: #718182; + display: block; + font-family: var(--font-geist-mono), monospace; + font-size: 9px; + letter-spacing: 0.08em; + margin-bottom: 8px; + text-transform: uppercase; +} + +.method-summary p { + color: #526263; + display: -webkit-box; + font-size: 12px; + line-height: 1.55; + margin-bottom: 22px; + overflow: hidden; + -webkit-box-orient: vertical; + -webkit-line-clamp: 3; +} + +.control-strip { + display: grid; + gap: 5px; + grid-template-columns: repeat(3, 1fr); + margin-top: auto; +} + +.control-strip span { + background: rgba(13, 23, 24, 0.06); + color: #657576; + font-family: var(--font-geist-mono), monospace; + font-size: 8px; + padding: 8px 5px; + text-align: center; + text-transform: uppercase; +} + +.control-strip span[data-state="yes"], +.control-strip span[data-state="high"] { + background: rgba(123, 224, 169, 0.24); + color: #17643c; +} + +.control-strip span[data-state="no"] { + background: rgba(241, 111, 81, 0.2); + color: #9a321c; +} + +.card-footer { + margin-top: 18px; +} + +.card-footer > span { + max-width: 62%; + overflow: hidden; + text-overflow: ellipsis; + white-space: nowrap; +} + +.card-footer button { + background: transparent; + border: 0; + color: #bd492e; + font-size: 10px; + font-weight: 700; + padding: 0; + text-transform: uppercase; +} + +.empty-state { + align-items: center; + border: 1px solid var(--line); + display: flex; + flex-direction: column; + justify-content: center; + min-height: 380px; + text-align: center; +} + +.empty-state strong { + color: rgba(13, 23, 24, 0.18); + font-family: Georgia, "Times New Roman", serif; + font-size: 100px; + font-weight: 400; + line-height: 1; +} + +.empty-state p { + color: #647475; +} + +.empty-state button { + background: var(--ink); + border: 0; + color: white; + padding: 12px 18px; +} + +.method-note { + padding: 112px clamp(24px, 8vw, 130px); +} + +.method-intro { + align-items: end; + display: flex; + gap: 80px; + justify-content: space-between; +} + +.method-intro > p { + color: rgba(255, 255, 255, 0.6); + font-size: 15px; + line-height: 1.65; + margin: 0; + max-width: 430px; +} + +.method-cloud { + display: grid; + gap: 1px; + grid-template-columns: repeat(4, 1fr); + margin-top: 72px; +} + +.method-cloud button { + align-items: end; + background: rgba(255, 255, 255, 0.04); + border: 1px solid rgba(255, 255, 255, 0.14); + color: white; + display: flex; + justify-content: space-between; + margin: 0 -1px -1px 0; + min-height: 120px; + padding: 20px; + text-align: left; + transition: background 160ms ease; +} + +.method-cloud button:hover, +.method-cloud button.featured { + background: rgba(123, 224, 169, 0.11); +} + +.method-cloud button span { + font-family: var(--font-geist-mono), monospace; + font-size: 11px; +} + +.method-cloud button strong { + color: var(--mint); + font-family: Georgia, "Times New Roman", serif; + font-size: 34px; + font-weight: 400; +} + +.fairness-section { + margin: 0 auto; + max-width: 1440px; + padding: 120px clamp(24px, 6vw, 92px); +} + +.fairness-heading h2 { + font-family: Georgia, "Times New Roman", serif; + font-size: clamp(40px, 5vw, 72px); + font-weight: 400; + letter-spacing: -0.055em; + line-height: 0.98; + max-width: 850px; +} + +.fairness-grid { + display: grid; + gap: 1px; + grid-template-columns: repeat(3, 1fr); + margin-top: 60px; +} + +.fairness-grid button { + background: rgba(255, 255, 255, 0.4); + border: 1px solid var(--line); + margin-right: -1px; + min-height: 270px; + padding: 28px; + text-align: left; +} + +.fairness-grid button:hover { + background: var(--paper-bright); +} + +.fairness-number { + align-items: center; + border-radius: 50%; + display: flex; + font-family: Georgia, "Times New Roman", serif; + font-size: 42px; + height: 86px; + justify-content: center; + margin-bottom: 34px; + width: 86px; +} + +.fairness-number.controlled { + background: rgba(123, 224, 169, 0.24); + color: #17643c; +} + +.fairness-number.unknown { + background: rgba(75, 203, 213, 0.17); + color: #16616a; +} + +.fairness-number.mismatch { + background: rgba(241, 111, 81, 0.2); + color: #9a321c; +} + +.fairness-grid strong { + display: block; + font-size: 15px; + margin-bottom: 10px; +} + +.fairness-grid p { + color: #5f7071; + font-size: 13px; + line-height: 1.55; + max-width: 310px; +} + +footer { + align-items: end; + gap: 60px; + padding-bottom: 62px; + padding-top: 62px; +} + +.footer-pitch { + align-items: flex-start; + gap: 22px; +} + +.footer-pitch h2 { + font-family: Georgia, "Times New Roman", serif; + font-size: clamp(28px, 3.2vw, 48px); + font-weight: 400; + letter-spacing: -0.04em; + line-height: 1; + margin-bottom: 14px; +} + +.footer-pitch p { + font-size: 13px; + line-height: 1.55; + max-width: 620px; +} + +.footer-action { + align-items: flex-end; + display: flex; + flex-direction: column; + flex-shrink: 0; + gap: 14px; +} + +.footer-action a { + background: var(--coral); + color: var(--ink); + font-weight: 700; + padding: 16px 20px; +} + +.footer-action span { + color: rgba(255, 255, 255, 0.42); + font-family: var(--font-geist-mono), monospace; + font-size: 8px; + letter-spacing: 0.06em; + text-transform: uppercase; +} + +.dialog-backdrop { + align-items: stretch; + background: rgba(5, 11, 12, 0.82); + display: flex; + inset: 0; + justify-content: flex-end; + position: fixed; + z-index: 100; +} + +.paper-dialog { + background: var(--paper-bright); + box-shadow: -24px 0 80px rgba(0, 0, 0, 0.26); + max-width: 820px; + overflow-y: auto; + padding: 42px clamp(28px, 5vw, 68px) 70px; + position: relative; + width: min(88vw, 820px); +} + +.dialog-close { + background: transparent; + border: 0; + color: #657576; + font-family: var(--font-geist-mono), monospace; + font-size: 10px; + position: absolute; + right: 24px; + text-transform: uppercase; + top: 24px; +} + +.dialog-header { + border-bottom: 1px solid var(--line); + padding: 24px 0 42px; +} + +.dialog-header > p:first-of-type { + color: #687879; + font-family: var(--font-geist-mono), monospace; + font-size: 10px; + margin: 22px 0; + text-transform: uppercase; +} + +.dialog-header h2 { + font-family: Georgia, "Times New Roman", serif; + font-size: clamp(48px, 7vw, 78px); + font-weight: 400; + letter-spacing: -0.06em; + line-height: 0.95; + margin-bottom: 18px; +} + +.dialog-header h3 { + color: #3f5051; + font-size: 16px; + font-weight: 500; + line-height: 1.45; + margin-bottom: 20px; +} + +.author-line { + color: #6b7a7b; + font-size: 11px; + line-height: 1.55; +} + +.dialog-section { + border-bottom: 1px solid var(--line); + padding: 36px 0; +} + +.product-config > div { + display: grid; + font-size: 12px; + gap: 10px; + grid-template-columns: 1fr 1fr 1fr; + padding: 10px 0; +} + +.product-config span { + color: #5e6f70; +} + +.dialog-grid { + border-bottom: 1px solid var(--line); + display: grid; + grid-template-columns: 1fr 1fr; +} + +.dialog-grid > section { + padding: 36px 30px 36px 0; +} + +.dialog-grid > section + section { + border-left: 1px solid var(--line); + padding-left: 30px; +} + +.dialog-grid p:not(.eyebrow), +.dialog-section p:not(.eyebrow) { + font-size: 13px; + line-height: 1.62; +} + +.dialog-grid small { + color: #677778; + display: block; + font-size: 10px; + line-height: 1.5; + margin-top: 18px; +} + +.tag-list { + display: flex; + flex-wrap: wrap; + gap: 6px; +} + +.tag-list span { + border: 1px solid var(--line); + font-family: var(--font-geist-mono), monospace; + font-size: 8px; + padding: 6px; +} + +.evidence-callout { + background: var(--ink); + color: white; + margin: 0 -1px; + padding: 38px; +} + +.evidence-callout .eyebrow { + color: var(--mint); +} + +.evidence-callout blockquote { + font-family: Georgia, "Times New Roman", serif; + font-size: 25px; + line-height: 1.42; + margin: 0; +} + +.control-grid { + display: grid; + gap: 8px; + grid-template-columns: repeat(3, 1fr); +} + +.control-grid > div { + background: rgba(13, 23, 24, 0.06); + display: flex; + flex-direction: column; + gap: 12px; + padding: 16px; +} + +.control-grid span { + color: #657576; + font-size: 9px; + text-transform: uppercase; +} + +.control-grid strong { + font-family: var(--font-geist-mono), monospace; + font-size: 12px; + text-transform: uppercase; +} + +.control-grid > div[data-state="yes"], +.control-grid > div[data-state="high"] { + background: rgba(123, 224, 169, 0.2); +} + +.control-grid > div[data-state="no"] { + background: rgba(241, 111, 81, 0.2); +} + +.evidence-notes .caveat-box { + background: rgba(241, 111, 81, 0.09); + padding-right: 24px; +} + +.dialog-actions { + display: flex; + gap: 12px; + padding-top: 36px; +} + +.dialog-actions a { + background: var(--ink); + color: white; + font-size: 12px; + padding: 14px 18px; +} + +.dialog-actions a + a { + background: transparent; + border: 1px solid var(--ink); + color: var(--ink); +} + +@media (max-width: 1120px) { + .filters { + grid-template-columns: repeat(4, 1fr); + } + + .filters fieldset { + grid-column: 1 / -1; + } + + .method-cloud { + grid-template-columns: repeat(3, 1fr); + } +} + +@media (max-width: 820px) { + .site-header nav { + gap: 16px; + } + + .site-header nav > a:not(.star-link) { + display: none; + } + + .filters { + grid-template-columns: 1fr 1fr; + } + + .method-intro { + align-items: flex-start; + flex-direction: column; + gap: 28px; + } + + .method-cloud { + grid-template-columns: repeat(2, 1fr); + } + + .fairness-grid { + grid-template-columns: 1fr; + } + + .fairness-grid button { + min-height: 220px; + } + + footer { + align-items: flex-start; + flex-direction: column; + } + + .footer-action { + align-items: flex-start; + } +} + +@media (max-width: 620px) { + .site-header { + padding-left: 18px; + padding-right: 18px; + } + + .star-link { + display: none; + } + + .filters { + grid-template-columns: 1fr; + } + + .filters fieldset { + overflow-x: auto; + } + + .segmented-control { + min-width: max-content; + } + + .method-cloud { + grid-template-columns: 1fr; + } + + .method-cloud button { + min-height: 94px; + } + + .paper-dialog { + width: 100vw; + } + + .dialog-grid, + .control-grid { + grid-template-columns: 1fr; + } + + .dialog-grid > section + section { + border-left: 0; + border-top: 1px solid var(--line); + padding-left: 0; + } + + .product-config > div { + grid-template-columns: 1fr; + } + + .dialog-actions { + flex-direction: column; + } +} diff --git a/website/app/layout.tsx b/website/app/layout.tsx new file mode 100644 index 0000000..9baca6c --- /dev/null +++ b/website/app/layout.tsx @@ -0,0 +1,76 @@ +import type { Metadata } from "next"; +import { Geist, Geist_Mono } from "next/font/google"; +import { headers } from "next/headers"; +import "./globals.css"; + +const geistSans = Geist({ + variable: "--font-geist-sans", + subsets: ["latin"], +}); + +const geistMono = Geist_Mono({ + variable: "--font-geist-mono", + subsets: ["latin"], +}); + +const title = "Awesome Claude Code & Codex Papers"; +const description = + "A readable, evidence-first index of methods that evaluate, analyze, or outperform production coding agents."; + +export async function generateMetadata(): Promise { + const requestHeaders = await headers(); + const forwardedHost = requestHeaders.get("x-forwarded-host")?.split(",")[0]; + const host = forwardedHost ?? requestHeaders.get("host") ?? "localhost:3000"; + const forwardedProtocol = requestHeaders.get("x-forwarded-proto")?.split(",")[0]; + const protocol = forwardedProtocol ?? (host.startsWith("localhost") ? "http" : "https"); + const origin = `${protocol}://${host}`; + const socialImage = new URL("/og.png", origin).toString(); + + return { + metadataBase: new URL(origin), + applicationName: "Agent Papers", + title, + description, + keywords: [ + "Claude Code", + "Codex CLI", + "coding agents", + "software engineering research", + "LLM agents", + ], + creator: "Awesome Claude Code & Codex Papers contributors", + publisher: "Awesome Claude Code & Codex Papers", + category: "research", + manifest: "/manifest.webmanifest", + icons: { icon: "/icon.svg" }, + robots: { index: true, follow: true }, + alternates: { canonical: origin }, + openGraph: { + title, + description, + type: "website", + siteName: "Agent Papers", + images: [{ url: socialImage, width: 1731, height: 909, alt: title }], + }, + twitter: { + card: "summary_large_image", + title, + description, + images: [socialImage], + }, + }; +} + +export default function RootLayout({ + children, +}: Readonly<{ + children: React.ReactNode; +}>) { + return ( + + + {children} + + + ); +} diff --git a/website/app/page.tsx b/website/app/page.tsx new file mode 100644 index 0000000..9901bfa --- /dev/null +++ b/website/app/page.tsx @@ -0,0 +1,11 @@ +import catalog from "@/data/catalog.json"; +import { CatalogExplorer, type Paper } from "./CatalogExplorer"; + +export default function Home() { + return ( + + ); +} diff --git a/website/data/catalog.json b/website/data/catalog.json new file mode 100644 index 0000000..534b870 --- /dev/null +++ b/website/data/catalog.json @@ -0,0 +1,1164 @@ +{ + "catalog_version": 1, + "reviewed_at": "2026-08-21", + "papers": [ + { + "id": "qlcoder-2026", + "title": "QLCoder: A Query Synthesizer For Static Analysis of Security Vulnerabilities", + "authors": [ + "Claire Wang", + "Ziyang Li", + "Saikat Dutta", + "Mayur Naik" + ], + "year": 2026, + "venue": "ICLR", + "publication_status": "main", + "classification": "direct", + "system": "QLCoder", + "paper_url": "https://proceedings.iclr.cc/paper_files/paper/2026/hash/2adf01ab15adde8820622f7f24bd516b-Abstract-Conference.html", + "artifact_url": "https://github.com/neuralprogram/qlcoder", + "artifact_status": "official", + "arxiv_id": "2511.08462", + "published_at": "2025-11-11", + "products": [ + { + "product": "claude-code", + "role": "baseline", + "model": "Claude Sonnet 4", + "version": "1.0.120" + } + ], + "task": { + "summary": "CodeQL query synthesis from CVE metadata", + "benchmark": "176 CVEs across 111 Java projects" + }, + "method": { + "summary": "CVE-grounded retrieval, AST guidance, CodeQL LSP tools, and iterative execution feedback", + "tags": [ + "retrieval", + "verifier-loop", + "static-analysis" + ] + }, + "evidence": { + "result": "Correct-query rate 53.4% versus 10% for Claude Code-only; F1 0.70 versus 0.048 for IRIS and 0.073 for CodeQL suites.", + "same_model": "unknown", + "same_budget": "unknown", + "strength": "high", + "claim_type": "quality", + "comparison_scope": "product-level", + "source_location": "Official abstract, main evaluation, and artifact paper environment", + "caveats": "Security-query synthesis is narrower than general software engineering." + } + }, + { + "id": "rpg-zerorepo-2026", + "title": "RPG: A Repository Planning Graph for Unified and Scalable Codebase Generation", + "authors": [ + "Jane Luo", + "Xin Zhang", + "Steven Liu", + "Jie Wu", + "Jianfeng Liu", + "Yiming Huang", + "Yangyu Huang", + "Chengyu Yin", + "Ying Xin", + "Yuefeng Zhan", + "Hao Sun", + "Qi Chen", + "Scarlett Li", + "Mao Yang" + ], + "year": 2026, + "venue": "ICLR", + "publication_status": "main", + "classification": "direct", + "system": "ZeroRepo", + "paper_url": "https://proceedings.iclr.cc/paper_files/paper/2026/file/9482f45fdd89aba9130bb04c44f788a9-Paper-Conference.pdf", + "artifact_url": "https://github.com/microsoft/RPG-ZeroRepo", + "artifact_status": "official", + "arxiv_id": "2509.16198", + "published_at": "2025-09-19", + "products": [ + { + "product": "claude-code", + "role": "baseline", + "model": "Claude 4 Sonnet", + "version": "not-reported" + }, + { + "product": "codex-cli", + "role": "baseline", + "model": "o3-pro", + "version": "not-reported" + } + ], + "task": { + "summary": "Repository-level codebase generation", + "benchmark": "RepoCraft" + }, + "method": { + "summary": "Persistent graph over features, functions, files, interfaces, and data flow with graph-guided generation and validation", + "tags": [ + "structured-state", + "repository-graph", + "dependency-aware-planning", + "test-feedback" + ] + }, + "evidence": { + "result": "ZeroRepo coverage 81.5% versus Claude Code 54.2% and Codex 28.4%; pass rate 69.7% versus Claude Code 33.9%.", + "same_model": "no", + "same_budget": "unknown", + "strength": "high", + "claim_type": "quality", + "comparison_scope": "product-level", + "source_location": "Section 4.3 and RepoCraft main-results table", + "caveats": "ZeroRepo uses o3-mini while the Claude Code baseline uses Claude 4 Sonnet, so model and harness effects are mixed." + } + }, + { + "id": "artemis-2026", + "title": "Comparing AI Agents to Cybersecurity Professionals in Real-World Penetration Testing", + "authors": [ + "Justin W. Lin", + "Eliot Krzysztof Jones", + "Donovan Julian Jasper", + "Ethan Jun-shen Ho", + "Anna Wu", + "Arnold Tianyi Yang", + "Neil Perry", + "Andy Zou", + "Matt Fredrikson", + "J. Zico Kolter", + "Percy Liang", + "Dan Boneh", + "Daniel E. Ho" + ], + "year": 2026, + "venue": "ICLR", + "publication_status": "main", + "classification": "direct", + "system": "ARTEMIS", + "paper_url": "https://arxiv.org/abs/2512.09882", + "artifact_url": "https://github.com/Stanford-Trinity/ARTEMIS", + "artifact_status": "official", + "arxiv_id": "2512.09882", + "published_at": "2025-12-10", + "products": [ + { + "product": "claude-code", + "role": "baseline", + "model": "Claude Sonnet 4", + "version": "not-reported" + }, + { + "product": "codex-cli", + "role": "baseline", + "model": "GPT-5", + "version": "not-reported" + } + ], + "task": { + "summary": "Long-horizon penetration testing in a live enterprise network", + "benchmark": "Approximately 8,000 hosts across 12 subnets" + }, + "method": { + "summary": "Supervisor with dynamic expert agents, recursive task decomposition, parallel exploration, context management, triage, and reporting", + "tags": [ + "multi-agent", + "dynamic-specialization", + "parallelism", + "memory", + "verifier-loop" + ] + }, + "evidence": { + "result": "ARTEMIS found 9 valid vulnerabilities with an 82% valid-submission rate, ranked second overall, and outperformed 9 of 10 human participants.", + "same_model": "unknown", + "same_budget": "no", + "strength": "medium", + "claim_type": "mixed", + "comparison_scope": "product-level", + "source_location": "Abstract and main penetration-testing results", + "caveats": "Runtime limits, model combinations, safety refusals, and product policies differ across systems." + } + }, + { + "id": "mlzero-2025", + "title": "MLZero: A Multi-Agent System for End-to-end Machine Learning Automation", + "authors": [ + "Haoyang Fang", + "Boran Han", + "Nick Erickson", + "Xiyuan Zhang", + "Su Zhou", + "Anirudh Dagar", + "Jiani Zhang", + "Ali Caner Turkmen", + "Cuixiong Hu", + "Huzefa Rangwala", + "Ying Nian Wu", + "Bernie Wang", + "George Karypis" + ], + "year": 2025, + "venue": "NeurIPS", + "publication_status": "main", + "classification": "direct", + "system": "MLZero", + "paper_url": "https://papers.neurips.cc/paper_files/paper/2025/hash/63ed15a46a143ff57484b38cd6b85d91-Abstract-Conference.html", + "artifact_url": "https://github.com/autogluon/autogluon-assistant", + "artifact_status": "official", + "arxiv_id": "2505.13941", + "published_at": "2025-05-20", + "products": [ + { + "product": "codex-cli", + "role": "baseline", + "model": "GPT-4.1 and o4-mini", + "version": "not-reported" + } + ], + "task": { + "summary": "End-to-end machine learning automation", + "benchmark": "MLE-Bench Lite and Multimodal AutoML Agent Benchmark" + }, + "method": { + "summary": "Hierarchical agents with multimodal perception, semantic and episodic memory, and a planning-coding-evaluation loop", + "tags": [ + "multi-agent", + "memory", + "verifier-loop", + "test-feedback" + ] + }, + "evidence": { + "result": "MLZero led MLE-Bench Lite with six gold medals and achieved 0.92 success on its multimodal benchmark; one appendix setting reports 6.5% errors versus 26.9% for Codex CLI.", + "same_model": "unknown", + "same_budget": "unknown", + "strength": "medium", + "claim_type": "quality", + "comparison_scope": "product-level", + "source_location": "Abstract, main benchmark results, and appendix error analysis", + "caveats": "Results concern machine-learning automation and should not be generalized to all software-engineering tasks." + } + }, + { + "id": "formact-2026", + "title": "FormAct: Agentic Source Editing for Rich-Format Document Generation", + "authors": [ + "Eugene J. Yu", + "Xingxing Zhang", + "Yuan Xia", + "Tao Ge", + "Xun Wang", + "FNU Kartik", + "Vishwas Suryanarayanan", + "Cheng Yang", + "Amanda Jiang", + "Jiayu Ding", + "Xiangyu Wong", + "Tengchao Lv", + "Lei Cui", + "Si-Qing Chen", + "Furu Wei", + "Sujian Li" + ], + "year": 2026, + "venue": "ICML", + "publication_status": "main", + "classification": "direct", + "system": "FormAct", + "paper_url": "https://openreview.net/forum?id=n7Ta0YEcgw", + "artifact_status": "not-found", + "products": [ + { + "product": "codex-cli", + "role": "baseline", + "model": "not-reported", + "version": "not-reported" + } + ], + "task": { + "summary": "Rich-format document generation and editing", + "benchmark": "RichDocBench and RichDocFuzz" + }, + "method": { + "summary": "HTML source editor, template retrieval, rendered-page review agent, iterative refinement, and edit-triggered context compression", + "tags": [ + "retrieval", + "context-reduction", + "verifier-loop", + "visual-review" + ] + }, + "evidence": { + "result": "Render correctness 4.81 versus 4.39 for multi-pass Codex; human rank-1 rate 0.760 versus 0.140.", + "same_model": "unknown", + "same_budget": "unknown", + "strength": "high", + "claim_type": "mixed", + "comparison_scope": "product-level", + "source_location": "Main comparison table and review-refinement ablation", + "caveats": "Codex has slightly higher content alignment, and the task is document formatting rather than source-code repair." + } + }, + { + "id": "agentic-harness-engineering-2026", + "title": "Agentic Harness Engineering: Observability-Driven Automatic Evolution of Coding-Agent Harnesses", + "authors": [ + "Jiahang Lin", + "Shichun Liu", + "Chengjun Pan", + "Lizhi Lin", + "Shihan Dou", + "Zhiheng Xi", + "Xuanjing Huang", + "Hang Yan", + "Zhenhua Han", + "Tao Gui", + "Yu-Gang Jiang" + ], + "year": 2026, + "venue": "arXiv", + "publication_status": "preprint", + "classification": "direct", + "system": "Agentic Harness Engineering", + "paper_url": "https://arxiv.org/abs/2604.25850", + "artifact_url": "https://github.com/china-qijizhifeng/agentic-harness-engineering", + "artifact_status": "official", + "arxiv_id": "2604.25850", + "published_at": "2026-04-28", + "products": [ + { + "product": "codex-cli", + "role": "baseline", + "model": "not-reported", + "version": "not-reported" + } + ], + "task": { + "summary": "Automatic evolution of coding-agent harnesses", + "benchmark": "Terminal-Bench 2 and SWE-bench Verified" + }, + "method": { + "summary": "Closed-loop harness evolution using component, trajectory, and decision observability with evidence-backed edits and rollback", + "tags": [ + "harness-evolution", + "observability", + "memory", + "verifier-loop" + ] + }, + "evidence": { + "result": "Terminal-Bench 2 pass@1 improves from 69.7 to 77.0, above a human-designed Codex-CLI harness at 71.9; transfer uses 12% fewer tokens on SWE-bench Verified.", + "same_model": "unknown", + "same_budget": "unknown", + "strength": "medium", + "claim_type": "mixed", + "comparison_scope": "product-level", + "source_location": "Abstract and Terminal-Bench 2 transfer and ablation results", + "caveats": "Preprint; model, harness, and evaluation-budget effects require careful separation." + } + }, + { + "id": "webdesigniter-2026", + "title": "WebDesignIter: Co-Evolving Design Knowledge for Repository-Level Front-End Code Generation", + "authors": [ + "Zheng Pei", + "Mingwei Liu", + "Zhenxi Chen", + "Zihao Wang", + "Yanlin Wang" + ], + "year": 2026, + "venue": "arXiv", + "publication_status": "preprint", + "classification": "direct", + "system": "WebDesignIter", + "paper_url": "https://arxiv.org/abs/2607.10621", + "artifact_url": "https://github.com/SYSUSELab/WebDesignIter", + "artifact_status": "official", + "arxiv_id": "2607.10621", + "published_at": "2026-07-12", + "products": [ + { + "product": "claude-code", + "role": "baseline", + "model": "not-reported", + "version": "not-reported" + }, + { + "product": "codex-cli", + "role": "baseline", + "model": "not-reported", + "version": "not-reported" + } + ], + "task": { + "summary": "Repository-level front-end code generation", + "benchmark": "Web-Bench" + }, + "method": { + "summary": "Persistent architecture and design knowledge graph, design-informed planning, targeted patches, and sandbox repair", + "tags": [ + "structured-state", + "repository-graph", + "retrieval", + "test-feedback" + ] + }, + "evidence": { + "result": "Average Pass@2 improves by 9.55 percentage points over existing baselines; removing design knowledge reduces Pass@1 by 11.4 points.", + "same_model": "unknown", + "same_budget": "unknown", + "strength": "medium", + "claim_type": "quality", + "comparison_scope": "product-level", + "source_location": "Abstract, main Web-Bench comparison, and design-knowledge ablation", + "caveats": "Front-end-specific benchmark and preprint status." + } + }, + { + "id": "prefactory-2026", + "title": "Prefactory: Automated Discovery and Application of Library-Adoption Refactorings", + "authors": [ + "Islem Bouzenia", + "Michael Pradel" + ], + "year": 2026, + "venue": "arXiv", + "publication_status": "preprint", + "classification": "direct", + "system": "Prefactory", + "paper_url": "https://arxiv.org/abs/2607.17211", + "artifact_status": "not-found", + "arxiv_id": "2607.17211", + "published_at": "2026-07-19", + "products": [ + { + "product": "codex-cli", + "role": "baseline", + "model": "not-reported", + "version": "not-reported" + } + ], + "task": { + "summary": "Discovery and application of library-adoption refactorings", + "benchmark": "PrefactoryBench" + }, + "method": { + "summary": "LLM-synthesized lexical and structural search heuristics, deterministic candidate ranking, targeted refactoring, and differential tests", + "tags": [ + "deterministic-search", + "static-analysis", + "test-feedback", + "verifier-loop" + ] + }, + "evidence": { + "result": "File-level detection 75 versus Codex 35; function-level detection 56 versus 32; 40 of 56 candidates yield test-validated refactorings.", + "same_model": "unknown", + "same_budget": "unknown", + "strength": "medium", + "claim_type": "quality", + "comparison_scope": "product-level", + "source_location": "Abstract and PrefactoryBench detection and validation results", + "caveats": "The strongest comparison concerns candidate detection, not universal end-to-end task success." + } + }, + { + "id": "rustprint-2026", + "title": "RustPrint: Documentation-Guided Agentic Codebase Migration from C to Rust", + "authors": [ + "Minh Le-Anh", + "Anh Nguyen Hoang", + "Bach Le", + "Nghi D. Q. Bui" + ], + "year": 2026, + "venue": "arXiv", + "publication_status": "preprint", + "classification": "direct", + "system": "RustPrint", + "paper_url": "https://arxiv.org/abs/2605.14634", + "artifact_status": "not-found", + "arxiv_id": "2605.14634", + "published_at": "2026-05-14", + "products": [ + { + "product": "claude-code", + "role": "baseline", + "model": "not-reported", + "version": "not-reported" + } + ], + "task": { + "summary": "Whole-codebase migration from C to Rust", + "benchmark": "Eight real C repositories from 11K to 84K lines of code" + }, + "method": { + "summary": "Architecture documentation blueprint, module and data-flow planning, compile feedback, documentation mismatch repair, and source-test translation", + "tags": [ + "structured-state", + "dependency-aware-planning", + "verifier-loop", + "test-feedback" + ] + }, + "evidence": { + "result": "In the reported Kimi-K2-Instruct setting, feature preservation is 93.26% versus 52.52% for agentic Claude Code; cross-evaluation test pass is 95.17% versus 79.85%.", + "same_model": "no", + "same_budget": "unknown", + "strength": "medium", + "claim_type": "quality", + "comparison_scope": "product-level", + "source_location": "Abstract and feature-preservation and cross-evaluation results", + "caveats": "The comparison mixes model and scaffold choices and is specific to C-to-Rust migration." + } + }, + { + "id": "repoomp-2026", + "title": "RepoOMP: Repository-Aware Hotspot OpenMP Parallelization via Dependency-Aware Context Reduction", + "authors": [ + "Yongjie Qian", + "Ke Gao", + "Zhibin Zhang", + "Shaohui Peng", + "Ling Li" + ], + "year": 2026, + "venue": "arXiv", + "publication_status": "preprint", + "classification": "direct", + "system": "RepoOMP", + "paper_url": "https://arxiv.org/abs/2608.05855", + "artifact_url": "https://github.com/Qlalq/RepoOMP_Simplified", + "artifact_status": "official", + "arxiv_id": "2608.05855", + "published_at": "2026-08-06", + "products": [ + { + "product": "claude-code", + "role": "baseline", + "model": "not-reported", + "version": "not-reported" + } + ], + "task": { + "summary": "Repository-aware OpenMP hotspot parallelization", + "benchmark": "951 hotspots including 330 accepted real-world hotspots" + }, + "method": { + "summary": "Multi-granularity dependency graph, rule-or-LLM hotspot routing, reduced transformation context, and compile/workload/speedup validation", + "tags": [ + "repository-graph", + "context-reduction", + "deterministic-search", + "performance-feedback", + "verifier-loop" + ] + }, + "evidence": { + "result": "Across nine detailed kernels, speedup improves 18% to 28% and token cost falls 47% to 68% relative to unstructured Claude Code.", + "same_model": "unknown", + "same_budget": "unknown", + "strength": "medium", + "claim_type": "mixed", + "comparison_scope": "product-level", + "source_location": "Abstract and nine-kernel cross-backbone comparison", + "caveats": "Domain-specific high-performance-computing task and preprint status." + } + }, + { + "id": "icat-agent-2026", + "title": "Unlocking Model Potentials Through Adaptive Multi-Agent Scaffolding for Efficient Issue Resolution", + "authors": [ + "Yang Chen", + "Aliya Ahmad", + "Yiheng Zhou", + "Reyhaneh Jabbarvand" + ], + "year": 2026, + "venue": "arXiv", + "publication_status": "preprint", + "classification": "direct", + "system": "icat-agent", + "paper_url": "https://arxiv.org/abs/2606.25514", + "artifact_status": "not-found", + "arxiv_id": "2606.25514", + "published_at": "2026-06-24", + "products": [ + { + "product": "claude-code", + "role": "baseline", + "model": "not-reported", + "version": "not-reported" + } + ], + "task": { + "summary": "Repository issue resolution", + "benchmark": "SWE-bench Verified and SWE-bench Pro" + }, + "method": { + "summary": "Event-based agent communication, issue-quality routing, parallel patching and validation, and exploratory fallback", + "tags": [ + "multi-agent", + "dynamic-specialization", + "parallelism", + "test-feedback" + ] + }, + "evidence": { + "result": "SWE-bench Verified improves 3.6 to 8.4 percentage points and SWE-bench Pro 6.3 to 18.5 points; average cost is $1.18 lower than multi-agent Claude Code.", + "same_model": "unknown", + "same_budget": "unknown", + "strength": "medium", + "claim_type": "mixed", + "comparison_scope": "product-level", + "source_location": "Abstract and SWE-bench Verified and Pro comparisons", + "caveats": "Exact model parity varies by reported configuration; preprint." + } + }, + { + "id": "co-coder-2026", + "title": "When Parallelism Pays Off: Cohesion-Aware Task Partitioning for Multi-Agent Coding", + "authors": [ + "Xu Yang", + "Lunyiu Nie", + "Ethan Chandra", + "Stanislav Gannutin", + "Fangru Lin", + "Swarat Chaudhuri" + ], + "year": 2026, + "venue": "arXiv", + "publication_status": "preprint", + "classification": "direct", + "system": "Co-Coder", + "paper_url": "https://arxiv.org/abs/2606.00953", + "artifact_url": "https://github.com/Flitternie/CoCoder", + "artifact_status": "official", + "arxiv_id": "2606.00953", + "published_at": "2026-05-31", + "products": [ + { + "product": "claude-code", + "role": "baseline", + "model": "not-reported", + "version": "Agent Teams" + } + ], + "task": { + "summary": "Parallel multi-agent coding", + "benchmark": "28 DevEval and CodeProjectEval tasks" + }, + "method": { + "summary": "Static dependency graph partitioning, structural hub isolation, community detection, and dependency-aware scheduling", + "tags": [ + "repository-graph", + "dependency-aware-planning", + "multi-agent", + "parallelism" + ] + }, + "evidence": { + "result": "Pass rate improves 14.0%, wall-clock speedup reaches 2.10x, and API cost falls 35% relative to Claude Code Agent Teams and simpler schedules.", + "same_model": "unknown", + "same_budget": "unknown", + "strength": "medium", + "claim_type": "mixed", + "comparison_scope": "product-level", + "source_location": "Abstract and DevEval and CodeProjectEval comparisons", + "caveats": "Small 28-task evaluation and preprint status." + } + }, + { + "id": "agents-md-impact-2026", + "title": "On the Impact of AGENTS.md Files on the Efficiency of AI Coding Agents", + "authors": [ + "Jai Lal Lulla", + "Seyedmoein Mohsenimofidi", + "Matthias Galster", + "Jie M. Zhang", + "Sebastian Baltes", + "Christoph Treude" + ], + "year": 2026, + "venue": "ICSE JAWs", + "publication_status": "workshop", + "classification": "direct", + "system": "AGENTS.md", + "paper_url": "https://conf.researchr.org/details/icse-2026/jaws-2026-papers/31/On-the-Impact-of-AGENTS-md-Files-on-the-Efficiency-of-AI-Coding-Agents", + "artifact_status": "not-found", + "arxiv_id": "2601.20404", + "published_at": "2026-01-28", + "products": [ + { + "product": "claude-code", + "role": "baseline", + "model": "not-reported", + "version": "not-reported" + }, + { + "product": "codex-cli", + "role": "baseline", + "model": "not-reported", + "version": "not-reported" + } + ], + "task": { + "summary": "Real pull-request tasks with and without repository instructions", + "benchmark": "10 repositories and 124 pull requests" + }, + "method": { + "summary": "Persistent repository-level build, test, style, and directory guidance in AGENTS.md", + "tags": [ + "repository-instructions", + "structured-state", + "context-reduction" + ] + }, + "evidence": { + "result": "Median runtime falls 28.64% and output tokens fall 16.58% with comparable completion behavior.", + "same_model": "yes", + "same_budget": "yes", + "strength": "high", + "claim_type": "efficiency", + "comparison_scope": "configuration-ablation", + "source_location": "Abstract and with-versus-without AGENTS.md results", + "caveats": "Workshop study and configuration intervention rather than a standalone agent." + } + }, + { + "id": "codegrep-2026", + "title": "CodeGrep: An RL-Trained Retrieval Agent for LLM Coding Agents", + "authors": [ + "Wuya Chen", + "Yihao Yang", + "Yang Cao", + "Yue Lin" + ], + "year": 2026, + "venue": "arXiv", + "publication_status": "preprint", + "classification": "related", + "system": "CodeGrep", + "paper_url": "https://arxiv.org/abs/2608.05886", + "artifact_status": "not-found", + "arxiv_id": "2608.05886", + "published_at": "2026-08-06", + "products": [ + { + "product": "claude-code", + "role": "evaluated", + "model": "not-reported", + "version": "Claude-Code-like agent" + } + ], + "task": { + "summary": "Repository retrieval for issue resolution", + "benchmark": "SWE-bench Verified" + }, + "method": { + "summary": "GRPO-trained 14B retrieval agent that issues multi-turn parallel grep, glob, and read operations for a frozen downstream coding agent", + "tags": [ + "retrieval", + "context-reduction", + "parallelism" + ] + }, + "evidence": { + "result": "Resolve rate 27.0% versus 25.8% without retrieval; resolved tasks use 15% fewer rounds and 19% fewer tokens.", + "same_model": "yes", + "same_budget": "unknown", + "strength": "contextual", + "claim_type": "mixed", + "comparison_scope": "component-level", + "source_location": "Abstract and frozen-agent retrieval comparison", + "caveats": "The clean numeric comparison is against a frozen no-retrieval downstream agent, not necessarily the released Claude Code CLI." + } + }, + { + "id": "scate-2026", + "title": "SCATE: Learning to Supervise Coding Agents for Cost-Effective Test Generation", + "authors": [ + "Sijia Gu", + "Noor Nashid", + "Ali Mesbah" + ], + "year": 2026, + "venue": "arXiv", + "publication_status": "preprint", + "classification": "related", + "system": "SCATE", + "paper_url": "https://arxiv.org/abs/2607.08983", + "artifact_status": "not-found", + "arxiv_id": "2607.08983", + "published_at": "2026-07-09", + "products": [ + { + "product": "claude-code", + "role": "evaluated", + "model": "not-reported", + "version": "not-reported" + } + ], + "task": { + "summary": "Automated test generation", + "benchmark": "Repository-level test-generation benchmark" + }, + "method": { + "summary": "Contextual-bandit supervisor that selects testing actions from current coverage and testability state", + "tags": [ + "test-feedback", + "verifier-loop" + ] + }, + "evidence": { + "result": "Line coverage improves 32.3% and branch coverage 30.9% over agent-only Gemini CLI; adaptation is also evaluated with Claude Code.", + "same_model": "unknown", + "same_budget": "unknown", + "strength": "contextual", + "claim_type": "quality", + "comparison_scope": "component-level", + "source_location": "Abstract and cross-agent adaptation experiment", + "caveats": "The abstract does not provide an equally complete numeric head-to-head against Claude Code." + } + }, + { + "id": "terminal-bench-2-2026", + "title": "Terminal-Bench 2.0: Advancing Agentic Terminal Intelligence through Better Evaluation and Verification", + "authors": [ + "Mike A. Merrill", + "Alexander G. Shaw", + "Nicholas Carlini", + "Boxuan Li", + "Harsh Raj", + "Ivan Bercovich", + "Lin Shi", + "Jeong Yeon Shin", + "Thomas Walshe", + "E. Kelly Buchanan", + "Junhong Shen", + "Guanghao Ye", + "Haowei Lin", + "Jason Poulos", + "Maoyu Wang", + "Marianna Nezhurina", + "Jenia Jitsev", + "Di Lu", + "Orfeas Menis Mastromichalakis", + "Zhiwei Xu", + "Zizhao Chen", + "Yue Liu", + "Robert Zhang", + "Leon Liangyu Chen", + "Anurag Kashyap", + "Jan-Lucas Uslu", + "Jeffrey Li", + "Jianbo Wu", + "Minghao Yan", + "Song Bian", + "Vedang Sharma", + "Ke Sun", + "Steven Dillmann", + "Akshay Anand", + "Andrew Lanpouthakoun", + "Bardia Koopah", + "Changran Hu", + "Etash Guha", + "Gabriel H. S. Dreiman", + "Jiacheng Zhu", + "Karl Krauth", + "Li Zhong", + "Niklas Muennighoff", + "Robert Amanfu", + "Shangyin Tan", + "Shreyas Pimpalgaonkar", + "Tushar Aggarwal", + "Xiangning Lin", + "Xin Lan", + "Xuandong Zhao", + "Yiqing Liang", + "Yuanli Wang", + "Zilong Wang", + "Changzhi Zhou", + "David Heineman", + "Hange Liu", + "Harsh Trivedi", + "John Yang", + "Junhong Lin", + "Manish Shetty", + "Michael Yang", + "Nabil Omi", + "Negin Raoof", + "Shanda Li", + "Terry Yue Zhuo", + "Wuwei Lin", + "Yiwei Dai", + "Yuxin Wang", + "Wenhao Chai", + "Shang Zhou", + "Dariush Wahdany", + "Ziyu She", + "Jiaming Hu", + "Zhikang Dong", + "Yuxuan Zhu", + "Sasha Cui", + "Ahson Saiyed", + "Arinbjörn Kolbeinsson", + "Jesse Hu", + "Christopher Michael Rytting", + "Ryan Marten", + "Yixin Wang", + "Alex Dimakis", + "Andy Konwinski", + "Ludwig Schmidt" + ], + "year": 2026, + "venue": "ICLR", + "publication_status": "main", + "classification": "evaluation", + "system": "Terminal-Bench 2.0", + "paper_url": "https://proceedings.iclr.cc/paper_files/paper/2026/file/444a3737adaee10d86ad2ef5f74468e6-Paper-Conference.pdf", + "artifact_url": "https://github.com/harbor-framework/terminal-bench-2", + "artifact_status": "official", + "arxiv_id": "2601.11868", + "published_at": "2026-01-17", + "products": [ + { + "product": "claude-code", + "role": "evaluated", + "model": "Claude Opus 4.5", + "version": "not-reported" + }, + { + "product": "codex-cli", + "role": "evaluated", + "model": "GPT-5.2", + "version": "not-reported" + } + ], + "task": { + "summary": "General terminal-agent evaluation", + "benchmark": "Terminal-Bench 2.0" + }, + "method": { + "summary": "Evaluation-only benchmark with stronger task verification and a neutral terminal scaffold", + "tags": [ + "verifier-loop" + ] + }, + "evidence": { + "result": "GPT-5.2 with Codex CLI scores 62.9; Claude Opus 4.5 scores 57.8 with Terminus 2 and 52.1 with Claude Code.", + "same_model": "unknown", + "same_budget": "unknown", + "strength": "high", + "claim_type": "mixed", + "comparison_scope": "benchmark-only", + "source_location": "Main agent and model results table", + "caveats": "Benchmark result; differences can reflect both model and harness, and no new method is proposed to beat the products." + } + }, + { + "id": "bountybench-2025", + "title": "BountyBench: Dollar Impact of AI Agent Attackers and Defenders on Real-World Cybersecurity Systems", + "authors": [ + "Andy K. Zhang", + "Joey Ji", + "Celeste Menders", + "Riya Dulepet", + "Thomas Qin", + "Ron Y. Wang", + "Junrong Wu", + "Kyleen Liao", + "Jiliang Li", + "Jinghan Hu", + "Sara Hong", + "Nardos Demilew", + "Shivatmica Murgai", + "Jason Tran", + "Nishka Kacheria", + "Ethan Ho", + "Denis Liu", + "Lauren McLane", + "Olivia Bruvik", + "Dai-Rong Han", + "Seungwoo Kim", + "Akhil Vyas", + "Cuiyuanxiu Chen", + "Ryan Li", + "Weiran Xu", + "Jonathan Z. Ye", + "Prerit Choudhary", + "Siddharth M. Bhatia", + "Vikram Sivashankar", + "Yuxuan Bao", + "Dawn Song", + "Dan Boneh", + "Daniel E. Ho", + "Percy Liang" + ], + "year": 2025, + "venue": "NeurIPS", + "publication_status": "dataset-benchmark", + "classification": "evaluation", + "system": "BountyBench", + "paper_url": "https://proceedings.neurips.cc/paper_files/paper/2025/hash/faed4276b52ef762879db4142655c699-Abstract-Datasets_and_Benchmarks_Track.html", + "artifact_url": "https://github.com/bountybench/bountybench", + "artifact_status": "official", + "arxiv_id": "2505.15216", + "published_at": "2025-05-21", + "products": [ + { + "product": "claude-code", + "role": "evaluated", + "model": "not-reported", + "version": "not-reported" + }, + { + "product": "codex-cli", + "role": "evaluated", + "model": "o3-high and o4-mini", + "version": "not-reported" + } + ], + "task": { + "summary": "Vulnerability detection, exploitation, and patching", + "benchmark": "BountyBench" + }, + "method": { + "summary": "Evaluation-only benchmark of offensive and defensive cybersecurity agents", + "tags": [ + "verifier-loop" + ] + }, + "evidence": { + "result": "Codex o3-high detects 12.5% and patches 90%; Claude Code patches 87.5% and exploits 57.5% in the reported settings.", + "same_model": "unknown", + "same_budget": "unknown", + "strength": "high", + "claim_type": "quality", + "comparison_scope": "benchmark-only", + "source_location": "Official abstract and agent task-results tables", + "caveats": "Benchmark-only evidence across different tasks and model configurations." + } + }, + { + "id": "engineering-pitfalls-2026", + "title": "Engineering Pitfalls in AI Coding Tools: An Empirical Study of Bugs in Claude Code, Codex, and Gemini CLI", + "authors": [ + "Ruixin Zhang", + "Wuyang Dai", + "Hung Viet Pham", + "Gias Uddin", + "Jinqiu Yang", + "Song Wang" + ], + "year": 2026, + "venue": "FSE Industry Track", + "publication_status": "conference", + "classification": "evaluation", + "system": "Bug taxonomy", + "paper_url": "https://conf.researchr.org/details/fse-2026/fse-2026-industry-papers/12/Engineering-Pitfalls-in-AI-Coding-Tools-An-Empirical-Study-of-Bugs-in-Claude-Code-C", + "artifact_status": "not-found", + "arxiv_id": "2603.20847", + "doi": "10.1145/3803437.3805213", + "published_at": "2026-03-21", + "products": [ + { + "product": "claude-code", + "role": "evaluated", + "model": "not-applicable", + "version": "multiple" + }, + { + "product": "codex-cli", + "role": "evaluated", + "model": "not-applicable", + "version": "multiple" + } + ], + "task": { + "summary": "Empirical analysis of product bug reports", + "benchmark": "More than 3,800 reported bugs" + }, + "method": { + "summary": "Evaluation-only manual taxonomy of functionality, integration, invocation, and command-execution failures", + "tags": [ + "observability" + ] + }, + "evidence": { + "result": "More than 67% of studied bugs concern functionality; API, integration, and configuration account for 36.9% of root causes.", + "same_model": "unknown", + "same_budget": "unknown", + "strength": "high", + "claim_type": "diagnostic", + "comparison_scope": "benchmark-only", + "source_location": "Abstract and root-cause, symptom, and workflow-stage findings", + "caveats": "Failure-taxonomy study; it does not propose an agent that outperforms the products." + } + }, + { + "id": "ticoder-2022", + "title": "Interactive Code Generation via Test-Driven User-Intent Formalization", + "authors": [ + "Shuvendu K. Lahiri", + "Sarah Fakhoury", + "Aaditya Naik", + "Georgios Sakkas", + "Saikat Chakraborty", + "Madanlal Musuvathi", + "Piali Choudhury", + "Curtis von Veh", + "Jeevana Priya Inala", + "Chenglong Wang", + "Jianfeng Gao" + ], + "year": 2022, + "venue": "AST at ICSE", + "publication_status": "workshop", + "classification": "historical", + "system": "TiCoder", + "paper_url": "https://arxiv.org/abs/2208.05950", + "artifact_url": "https://github.com/microsoft/TiCoder", + "artifact_status": "official", + "arxiv_id": "2208.05950", + "published_at": "2022-08-11", + "products": [ + { + "product": "openai-codex-model", + "role": "historical-baseline", + "model": "OpenAI Codex", + "version": "not-reported" + } + ], + "task": { + "summary": "Interactive function-level code generation", + "benchmark": "MBPP and HumanEval" + }, + "method": { + "summary": "Generate tests to formalize user intent, collect lightweight feedback, and rank or prune candidate programs", + "tags": [ + "test-feedback", + "verifier-loop" + ] + }, + "evidence": { + "result": "With one to five simulated user queries, Codex pass@1 gains 22.49 to 37.71 points on MBPP and 24.79 to 53.98 points on HumanEval.", + "same_model": "yes", + "same_budget": "no", + "strength": "high", + "claim_type": "quality", + "comparison_scope": "historical-model", + "source_location": "MBPP and HumanEval evaluation section", + "caveats": "This is the historical OpenAI Codex model, not the modern Codex CLI product." + } + } + ] +} diff --git a/website/eslint.config.mjs b/website/eslint.config.mjs new file mode 100644 index 0000000..14f59dd --- /dev/null +++ b/website/eslint.config.mjs @@ -0,0 +1,41 @@ +import { defineConfig, globalIgnores } from "eslint/config"; +import eslint from "@eslint/js"; +import next from "@next/eslint-plugin-next"; +import jsxA11y from "eslint-plugin-jsx-a11y"; +import react from "eslint-plugin-react"; +import reactHooks from "eslint-plugin-react-hooks"; +import globals from "globals"; +import tseslint from "typescript-eslint"; + +const eslintConfig = defineConfig([ + globalIgnores([ + ".next/**", + "dist/**", + "out/**", + "build/**", + "next-env.d.ts", + ]), + eslint.configs.recommended, + ...tseslint.configs.recommended, + react.configs.flat.recommended, + react.configs.flat["jsx-runtime"], + reactHooks.configs.flat["recommended-latest"], + jsxA11y.flatConfigs.recommended, + next.configs["core-web-vitals"], + { + languageOptions: { + globals: { + ...globals.browser, + ...globals.node, + ...globals.serviceworker, + }, + }, + settings: { + react: { + version: "detect", + }, + }, + }, +]); + +export default eslintConfig; diff --git a/website/next-env.d.ts b/website/next-env.d.ts new file mode 100644 index 0000000..c986d49 --- /dev/null +++ b/website/next-env.d.ts @@ -0,0 +1,5 @@ +import "vinext/types"; +import "./.next/types/routes.d.ts"; + +// NOTE: This file should not be edited +// see https://nextjs.org/docs/app/api-reference/config/typescript for more information. diff --git a/website/next.config.ts b/website/next.config.ts new file mode 100644 index 0000000..e9ffa30 --- /dev/null +++ b/website/next.config.ts @@ -0,0 +1,7 @@ +import type { NextConfig } from "next"; + +const nextConfig: NextConfig = { + /* config options here */ +}; + +export default nextConfig; diff --git a/website/package-lock.json b/website/package-lock.json new file mode 100644 index 0000000..72f6caa --- /dev/null +++ b/website/package-lock.json @@ -0,0 +1,8769 @@ +{ + "name": "awesome-claude-code-codex-papers-site", + "version": "0.1.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "awesome-claude-code-codex-papers-site", + "version": "0.1.0", + "dependencies": { + "react": "^19.2.8", + "react-dom": "^19.2.8" + }, + "devDependencies": { + "@cloudflare/vite-plugin": "^1.53.1", + "@eslint/js": "9.39.4", + "@next/eslint-plugin-next": "16.2.6", + "@openai/sites-vite-plugin": "0.1.0", + "@tailwindcss/postcss": "4.2.1", + "@types/node": "22.19.19", + 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+ "license": "MIT", + "engines": { + "node": ">=18.0.0" + }, + "peerDependencies": { + "zod": "^3.25.0 || ^4.0.0" + } + } + } +} diff --git a/website/package.json b/website/package.json new file mode 100644 index 0000000..bc3261f --- /dev/null +++ b/website/package.json @@ -0,0 +1,44 @@ +{ + "name": "awesome-claude-code-codex-papers-site", + "version": "0.1.0", + "private": true, + "engines": { + "node": ">=22.13.0" + }, + "scripts": { + "dev": "WRANGLER_LOG_PATH=.wrangler/wrangler.log vinext dev", + "build": "WRANGLER_LOG_PATH=.wrangler/wrangler.log vinext build", + "start": "WRANGLER_LOG_PATH=.wrangler/wrangler.log vinext start", + "test": "npm run build && node --test tests/rendered-html.test.mjs", + "lint": "eslint . --ignore-pattern dist --ignore-pattern .next" + }, + "dependencies": { + "react": "^19.2.8", + "react-dom": "^19.2.8" + }, + "devDependencies": { + "@cloudflare/vite-plugin": "^1.53.1", + "@eslint/js": "9.39.4", + "@next/eslint-plugin-next": "16.2.6", + "@openai/sites-vite-plugin": "0.1.0", + "@tailwindcss/postcss": "4.2.1", + "@types/node": "22.19.19", + "@types/react": "19.2.14", + "@types/react-dom": "19.2.3", + "@vitejs/plugin-react": "^6.1.0", + "@vitejs/plugin-rsc": "^0.5.34", + "eslint": "9.39.4", + "eslint-plugin-jsx-a11y": "6.10.2", + "eslint-plugin-react": "7.37.5", + "eslint-plugin-react-hooks": "7.1.1", + "globals": "16.4.0", + "react-server-dom-webpack": "^19.2.8", + "tailwindcss": "4.2.1", + "typescript": "5.9.3", + "typescript-eslint": "8.59.3", + "vinext": "^1.0.0-beta.8", + "vite": "^8.2.2", + "wrangler": "^4.125.0" + }, + "type": "module" +} diff --git a/website/postcss.config.mjs b/website/postcss.config.mjs new file mode 100644 index 0000000..61e3684 --- /dev/null +++ b/website/postcss.config.mjs @@ -0,0 +1,7 @@ +const config = { + plugins: { + "@tailwindcss/postcss": {}, + }, +}; + +export default config; diff --git a/website/public/icon.svg b/website/public/icon.svg new file mode 100644 index 0000000..042288c --- /dev/null +++ b/website/public/icon.svg @@ -0,0 +1,5 @@ + + + + + diff --git a/website/public/manifest.webmanifest b/website/public/manifest.webmanifest new file mode 100644 index 0000000..cca3b5a --- /dev/null +++ b/website/public/manifest.webmanifest @@ -0,0 +1,16 @@ +{ + "name": "Awesome Claude Code & Codex Papers", + "short_name": "Agent Papers", + "description": "Evidence-first research on production coding agents.", + "start_url": "/", + "display": "standalone", + "background_color": "#f1eee5", + "theme_color": "#0d1718", + "icons": [ + { + "src": "/icon.svg", + "sizes": "any", + "type": "image/svg+xml" + } + ] +} diff --git a/website/public/og.png b/website/public/og.png new file mode 100644 index 0000000..0ca0161 Binary files /dev/null and b/website/public/og.png differ diff --git a/website/public/robots.txt b/website/public/robots.txt new file mode 100644 index 0000000..c2a49f4 --- /dev/null +++ b/website/public/robots.txt @@ -0,0 +1,2 @@ +User-agent: * +Allow: / diff --git a/website/tests/rendered-html.test.mjs b/website/tests/rendered-html.test.mjs new file mode 100644 index 0000000..8ff6c9a --- /dev/null +++ b/website/tests/rendered-html.test.mjs @@ -0,0 +1,69 @@ +import assert from "node:assert/strict"; +import { readFile } from "node:fs/promises"; +import test from "node:test"; + +async function render(url = "https://papers.example.test/") { + const workerUrl = new URL("../dist/server/index.js", import.meta.url); + workerUrl.searchParams.set("test", `${process.pid}-${Date.now()}`); + const { default: worker } = await import(workerUrl.href); + const requestUrl = new URL(url); + + return worker.fetch( + new Request(url, { + headers: { + accept: "text/html", + host: requestUrl.host, + "x-forwarded-host": requestUrl.host, + "x-forwarded-proto": requestUrl.protocol.slice(0, -1), + }, + }), + { + ASSETS: { + fetch: async () => new Response("Not found", { status: 404 }), + }, + }, + { + waitUntil() {}, + passThroughOnException() {}, + }, + ); +} + +test("server-renders the finished research catalog", async () => { + const response = await render(); + assert.equal(response.status, 200); + assert.match(response.headers.get("content-type") ?? "", /^text\/html\b/i); + + const html = await response.text(); + assert.match(html, /Awesome Claude Code & Codex Papers<\/title>/i); + assert.match(html, /What actually beats/); + assert.match(html, /Claude Code & Codex\?/); + assert.match(html, /QLCoder/); + assert.match(html, /Star the repository/); + assert.match(html, /https:\/\/github\.com\/MicroMilo\/awesome-claude-code-codex-papers/); + assert.doesNotMatch(html, /codex-preview|react-loading-skeleton|Your site is taking shape/i); +}); + +test("emits host-aware social metadata", async () => { + const response = await render("https://catalog.example.org/"); + const html = await response.text(); + + assert.match( + html, + /<meta[^>]+property="og:image"[^>]+content="https:\/\/catalog\.example\.org\/og\.png"/i, + ); + assert.match(html, /<meta[^>]+name="twitter:card"[^>]+content="summary_large_image"/i); + assert.match( + html, + /<meta[^>]+name="twitter:image"[^>]+content="https:\/\/catalog\.example\.org\/og\.png"/i, + ); +}); + +test("site catalog mirrors the repository JSON export", async () => { + const [siteCatalog, repositoryCatalog] = await Promise.all([ + readFile(new URL("../data/catalog.json", import.meta.url), "utf8"), + readFile(new URL("../../data/papers.json", import.meta.url), "utf8"), + ]); + + assert.deepEqual(JSON.parse(siteCatalog), JSON.parse(repositoryCatalog)); +}); diff --git a/website/tsconfig.json b/website/tsconfig.json new file mode 100644 index 0000000..9c891d2 --- /dev/null +++ b/website/tsconfig.json @@ -0,0 +1,29 @@ +{ + "compilerOptions": { + "target": "ES2017", + "lib": ["dom", "dom.iterable", "esnext"], + "allowJs": true, + "skipLibCheck": true, + "strict": true, + "noEmit": true, + "esModuleInterop": true, + "module": "esnext", + "moduleResolution": "bundler", + "resolveJsonModule": true, + "isolatedModules": true, + "jsx": "react-jsx", + "incremental": true, + "paths": { + "@/*": ["./*"] + } + }, + "include": [ + "next-env.d.ts", + "**/*.ts", + "**/*.tsx", + ".next/types/**/*.ts", + ".next/dev/types/**/*.ts", + "**/*.mts" + ], + "exclude": ["node_modules"] +} diff --git a/website/vite.config.ts b/website/vite.config.ts new file mode 100644 index 0000000..3e29ab1 --- /dev/null +++ b/website/vite.config.ts @@ -0,0 +1,59 @@ +import { sites } from "@openai/sites-vite-plugin"; +import vinext from "vinext"; +import { defineConfig } from "vite"; +import hostingConfig from "./.openai/hosting.json" with { type: "json" }; + +const SITE_CREATOR_PLACEHOLDER_DATABASE_ID = + "00000000-0000-4000-8000-000000000000"; + +const { d1, r2 } = hostingConfig; + +// macOS Seatbelt blocks FSEvents, so Codex previews need polling for HMR. +const isCodexSeatbeltSandbox = process.env.CODEX_SANDBOX === "seatbelt"; + +const localBindingConfig = { + main: "./worker/index.ts", + compatibility_flags: ["nodejs_compat"], + d1_databases: d1 + ? [ + { + binding: d1, + database_name: "site-creator-d1", + database_id: SITE_CREATOR_PLACEHOLDER_DATABASE_ID, + }, + ] + : [], + r2_buckets: r2 + ? [ + { + binding: r2, + bucket_name: "site-creator-r2", + }, + ] + : [], +}; + +export default defineConfig(async () => { + // Keep Wrangler and Miniflare state project-local. These are non-secret tool + // settings; application environment belongs in ignored `.env*` files. + process.env.WRANGLER_WRITE_LOGS ??= "false"; + process.env.WRANGLER_LOG_PATH ??= ".wrangler/logs"; + process.env.MINIFLARE_REGISTRY_PATH ??= ".wrangler/registry"; + + // Wrangler snapshots its log path while the Cloudflare plugin is imported. + const { cloudflare } = await import("@cloudflare/vite-plugin"); + + return { + server: isCodexSeatbeltSandbox + ? { watch: { useFsEvents: false, usePolling: true } } + : undefined, + plugins: [ + vinext(), + sites(), + cloudflare({ + viteEnvironment: { name: "rsc", childEnvironments: ["ssr"] }, + config: localBindingConfig, + }), + ], + }; +}); diff --git a/website/worker/index.ts b/website/worker/index.ts new file mode 100644 index 0000000..b3cd137 --- /dev/null +++ b/website/worker/index.ts @@ -0,0 +1,47 @@ +/** Cloudflare Worker entry point for the vinext-starter template. */ +import { handleImageOptimization, DEFAULT_DEVICE_SIZES, DEFAULT_IMAGE_SIZES } from "vinext/server/image-optimization"; +import handler from "vinext/server/app-router-entry"; + +interface Env { + ASSETS: Fetcher; + DB: D1Database; + IMAGES: { + input(stream: ReadableStream): { + transform(options: Record<string, unknown>): { + output(options: { format: string; quality: number }): Promise<{ response(): Response }>; + }; + }; + }; +} + +interface ExecutionContext { + waitUntil(promise: Promise<unknown>): void; + passThroughOnException(): void; +} + +// Image security config. SVG sources with .svg extension auto-skip the +// optimization endpoint on the client side (served directly, no proxy). +// To route SVGs through the optimizer (with security headers), set +// dangerouslyAllowSVG: true in next.config.js and uncomment below: +// const imageConfig: ImageConfig = { dangerouslyAllowSVG: true }; + +const worker = { + async fetch(request: Request, env: Env, ctx: ExecutionContext): Promise<Response> { + const url = new URL(request.url); + + if (url.pathname === "/_vinext/image") { + const allowedWidths = [...DEFAULT_DEVICE_SIZES, ...DEFAULT_IMAGE_SIZES]; + return handleImageOptimization(request, { + fetchAsset: (path) => env.ASSETS.fetch(new Request(new URL(path, request.url))), + transformImage: async (body, { width, format, quality }) => { + const result = await env.IMAGES.input(body).transform(width > 0 ? { width } : {}).output({ format, quality }); + return result.response(); + }, + }, allowedWidths); + } + + return handler.fetch(request, env, ctx); + }, +}; + +export default worker;