github-release-prep
Skill3 starsChanged 8 months agoMITView on GitHub
Use when preparing a project for public GitHub release and you need to verify docs, licenses, notices, examples, repository hygiene, and release readiness.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- ryanduguid/github-agent-skillstheir own version, first seen Oct 30, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- ryanduguid/github-agent-skills★ 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
- latex-postersSkill
- literature-reviewSkill
- markdown-mermaid-writingSkill
- markitdownSkill
- matplotlibSkill
- modalSkill
- networkxSkill
- paper-to-codeSkill
- peer-reviewSkill
- plotlySkill
- polarsSkill
- pytorch-lightningSkill
- pyzoteroSkill
- repo-cleanupSkill
- 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
8 rules. About 0 are common, 8 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈8
Distinctive · estimate
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 making a repo public on GitHub
- Distinctive: line 13
before tagging a first release or sharing with external users
- Distinctive: line 14
when checking whether docs, licensing, and examples are complete
- Distinctive: line 15
when converting an internal research repo into a public artifact
- Distinctive: line 33
Verify the project story, audience, and minimal runnable entry point.
- Distinctive: line 34
Check README, docs, examples, and environment instructions.
- Distinctive: line 41
do not assume internal code or data is publishable
- Distinctive: line 42
treat missing attribution or unclear licensing as blockers
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Purpose
Prepare a repository for public release without leaking private material or publishing an incoherent project.
When To Use
- before making a repo public on GitHub
- before tagging a first release or sharing with external users
- when checking whether docs, licensing, and examples are complete
- when converting an internal research repo into a public artifact
Inputs
- repository state and release target
- current README, docs, notices, and attribution files
- known restrictions on data, checkpoints, credentials, or third-party assets
Outputs
- release-readiness checklist
- documentation and legal gap list
- example/demo packaging checklist
- release note outline and final blocking issues
- explicit publish versus do-not-publish inventory
Workflow
- Verify the project story, audience, and minimal runnable entry point.
- Check README, docs, examples, and environment instructions.
- Audit license, notice, attribution, secrets, data, and model assets.
- Confirm that the visible repository structure matches the public story.
- Produce final blockers before release instead of assuming readiness.
Constraints
- do not assume internal code or data is publishable
- treat missing attribution or unclear licensing as blockers
- separate polish issues from hard release blockers
- optimize for public clarity, not internal convenience
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.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
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.

