repo-cleanup
Skill3 starsChanged 8 months agoMITView on GitHub
Use when a research or prototype repository has become messy and you need a disciplined cleanup plan for structure, naming, docs, unused files, configs, and reproducibility hygiene.
6 other projects use a version of this.
Adopted by
Most recently taken up by
- itgenius-au/skills-librarytheir own version, first seen Nov 1, 2026
- sreejithraman/SreeStacktheir own version, first seen Oct 27, 2026
- EJRyan89/coding-agent-skillstheir own version, first seen Oct 17, 2026
- Sassy-Dog/skillstheir own version, first seen Oct 8, 2026
- heffrey/claude-skillstheir own version, first seen Apr 21, 2026
- henry-1981/context-first-harnesstheir own version, first seen Apr 19, 2026
Other versions6 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 6
- EJRyan89/coding-agent-skills★ 2same name
- heffrey/claude-skills★ 1same name
- itgenius-au/skills-library★ 1same name
- Sassy-Dog/skills★ 1same name
- sreejithraman/SreeStack★ 1same name
- henry-1981/context-first-harness★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository43 other files it gives its agents.
- agent-codingSkill
- benchmark-designSkill
- citation-managementSkill
- code-reproductionSkill
- code-to-paperSkill
- daskSkill
- experiment-trackingSkill
- exploratory-data-analysisSkill
- get-available-resourcesSkill
- github-release-prepSkill
- latex-postersSkill
- literature-reviewSkill
- markdown-mermaid-writingSkill
- markitdownSkill
- matplotlibSkill
- modalSkill
- networkxSkill
- paper-to-codeSkill
- peer-reviewSkill
- plotlySkill
- polarsSkill
- pytorch-lightningSkill
- pyzoteroSkill
- research-planningSkill
- reviewer-responseSkill
- scholar-evaluationSkill
- scientific-critical-thinkingSkill
- scientific-schematicsSkill
- scientific-slidesSkill
- scientific-visualizationSkill
- scientific-writingSkill
- scikit-learnSkill
- seabornSkill
- shapSkill
- stable-baselines3Skill
- statistical-analysisSkill
- statsmodelsSkill
- sympySkill
- torch-geometricSkill
- transformersSkill
- umap-learnSkill
- vaexSkill
- venue-templatesSkill
The file
We split this skill into the rules it gives an agent
5 rules. 0 are common, 5 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 5 edited versions we read keep these.
5
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 12
before public release or collaborator handoff
- Distinctive: line 13
after a rapid prototyping phase left the repo inconsistent
- Distinctive: line 14
when folders, scripts, and outputs have become hard to navigate
- Distinctive: line 15
when experiment artifacts and source code are mixed carelessly
- Distinctive: line 41
do not assume generated files are disposable without checking
“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Purpose
Improve repository clarity so code, experiments, and documents are easier to understand and maintain.
When To Use
- before public release or collaborator handoff
- after a rapid prototyping phase left the repo inconsistent
- when folders, scripts, and outputs have become hard to navigate
- when experiment artifacts and source code are mixed carelessly
Inputs
- repository layout and current file structure
- known pain points, stale outputs, and documentation gaps
- any constraints about files that must not be touched
Outputs
- cleanup plan ordered by safety and impact
- proposed directory and naming normalization
- list of stale, duplicated, or misplaced files
- documentation gaps and configuration hygiene fixes
- explicit separation of safe cleanup versus risky cleanup
Workflow
- Inspect the repo structure before proposing moves.
- Identify clutter, ambiguity, and unsafe mixing of source and generated outputs.
- Group cleanup work into structure, naming, docs, configs, and artifacts.
- Separate non-destructive cleanup from anything that needs confirmation.
- Produce a minimal end state that is easier to release and maintain.
Constraints
- do not assume generated files are disposable without checking
- separate cleanup suggestions from destructive actions
- preserve provenance for experiment outputs that may still matter
- favor clear structure over cosmetic churn
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
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Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.