Academic repo analyzer
Quick-understanding doc for ML/DL repositories — task type, stack, architecture, and figure-worthy innovations. Use when the user wants repo analysis, 仓库分析, or to understand a codebase before figure planning.From its SKILL.md
npx -y skills add Azhi-ss/academic-figure-skills --skill academic-repo-analyzerAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
SKILL.md
2.8 KB, 623 tokens by cl100k_base, as published. Nobody here has run it
Academic Repo Analyzer
Produce a 仓库快速理解文档 for downstream figure planning.
Keywords: → keywords.md
Missing info: → ../docs/missing-info-policy.md
Input Contract
- Prefer: repo path, README, deps, entry scripts, model files, configs
- Minimum: any one of README / entry script / model file
- Missing: partial analysis with 推断 / 待确认
Output Contract — Quick Understanding Doc
- overview (name, task, framework, architecture one-liner)
- completeness block
- stack details
- model / algorithm notes
- train / inference flow (or “evidence insufficient”)
- figure suggestions for paper-analyzer
Steps
Step 1: Scan structure
Locate README, dependency files, entry scripts (train|main|eval|inference), configs/, models|networks|src/, data loaders.
Done when: tree of key paths exists and each must-read class is read or marked missing.
Step 2: Task + stack
Use keywords.md. Classify task type and framework from imports, deps, and paths.
Done when: task type + primary framework are stated with file evidence.
Step 3: Architecture + algorithms
From model files: backbone family, key modules, losses, training tricks. Prefer evidence over naming guesses.
Done when: architecture summary cites concrete classes/files, or is marked 推断.
Step 4: Emit quick-understanding doc
# 仓库快速理解文档
## 仓库概览
| 项目 | 内容 |
| 仓库名称 / 任务类型 / 核心框架 / 主要架构 / 一句话描述 | ... |
## 信息完整度说明
## 技术栈详情
## 模型架构分析
## 工作流程
## 配图建议(→ paper-analyzer)
Done when: Output Contract fields are filled; figure suggestions list concrete types (framework / arch / module / …).
Sparse-input cases
| gap | action |
|---|---|
| no README | infer from code; label as structure-inferred |
| no entry scripts | module-level understanding only |
| no model files | stack/task only; soft architecture language |
| huge repo | sample top-level + 3–5 core files; mark limited sample |
| almost nothing | pre-analysis + minimum materials list (README → deps → entry → model → config) |
Tooling cues
Prefer the environment’s file/search tools. Typical digs: dependency files, class.*Model|Network|Transformer, loss|criterion, model package entrypoints.
Stop
Stop when the quick-understanding doc is delivered. Suggest paper-analyzer only if the user wants figure planning next.
What ships with it: 6 files
31.9 KB alongside SKILL.md, 3 of them executable
references/
- missing-info-policy.md1.1 KB
- palettes.md14.2 KB
scripts/
- create_sparse_fixture.pyruns1.4 KB
- fetch_benchmark_repos.pyruns2.8 KB
- run_repo_benchmarks.pyruns10.2 KB
- keywords.md2.2 KB