paper-reproduction
paper-reproduction is a Model training & evaluation skill for AI agents, published by WUBING2023 in the ReproRun repository on GitHub. Skillspace rates paper-reproduction D (67/100) and it passed the safety scan; the rating is based on static analysis only.
Use whenever the user wants to reproduce, replicate, or verify results from an academic paper — especially ML/CV/NLP papers with public GitHub repos and Python codebases. Triggers on: 复现, reproduce, replicate, 复现论文, 跑论文代码, verify results, paper reproduction, 验证实验结果, 论文复现, check if a paper's results are real, run this paper's code, reproduce table X from paper Y. Handles the full pipeline: read paper → find code & data → build environment → smoke test → full run → compare results against paper claims. Even if the user only mentions a paper title without a PDF, invoke this skill — it will search for the PDF automatically.
- Grade
- D
- Quality
- 67 / 100
- Safety
- Passed
- GitHub stars
- 41
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 76 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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