github-publisher
Skill1 starsChanged 21 days agoMITView on GitHub
Use when a user wants to publish or update a Skill or project on GitHub. Default to a short, change-scoped release flow; invoke engineering, performance or Token analysis only when requested or justified. Publish only after concrete confirmation.
4 other projects use a version of this.
Adopted by
Most recently taken up by
- AlekseiUL/heisenberg-team-GPTtheir own version, first seen Nov 1, 2026
- AlekseiUL/heisenberg-teamtheir own version, first seen Nov 1, 2026
- shimenghan6/claude-code-startertheir own version, first seen Jul 22, 2026
- xiaomoBoy/github-publishertheir own version, first seen May 25, 2026
Other versions4 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 4
- AlekseiUL/heisenberg-team★ 17same name
- AlekseiUL/heisenberg-team-GPT★ 9same name
- xiaomoBoy/github-publisher★ 4same name
- shimenghan6/claude-code-starter★ 1same 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.
The file
We split this skill into the rules it gives an agent
6 rules. About 0 are common, 2 are distinctive, and 4 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 16
Do not automatically run engineering scores, performance/Token benchmarks, optimization, full acceptance, repeated model comparisons or …
- Very specific: line 22
Understand / diagnose: read references/project-analysis.md.
- Very specific: line 25
Prepare / publish: use the short default above.
- Distinctive: line 33
Use existing runtimes and native commands.
- Very specific: line 41
Use actual model/elapsed/call metrics when available.
- Very specific: line 43
Follow the execution-efficiency rules in references/project-analysis.md without reducing required checks.
≈ “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
GitHub Publisher
Help the user publish the requested project with proportionate checks and concrete authorization. Preserve useful existing structure and documentation.
Default: short publication flow
Read references/pre-publish-flow.md for the default route: understand the request and diff → relevant release checks → show account, repository, branch, exact commits, candidate digest and actions → wait for explicit confirmation → execute only approved actions and verify. Read references/authorization.md for scope; reuse unchanged identity decisions under references/review-decisions.md, never as push permission.
Do not automatically run engineering scores, performance/Token benchmarks, optimization, full acceptance, repeated model comparisons or all-platform checks. Do not rewrite a satisfactory README or regenerate an unchanged approved preview just to release. Existing project-required CI/tests and known blockers still apply.
Optional subprocesses require a concrete trigger. State the issue, affected scope, expected work/cost and stop point before starting; obtain missing authorization for execution or edits. Use existing session authorization when it already covers that scope. Return to the publication flow after the relevant result; do not chain unrelated subprocesses. Performance suspicion alone permits proposing a measurement, not an expensive benchmark.
Select the requested route first
- Understand / diagnose: read
references/project-analysis.md; inspect the target's own entry point, source and tests. Finish with an evidence-based report. Do not start rewriting README, migrating directories or preparing screenshots unless requested. - Test: inspect the target's native test commands and their effects. Use existing tools, scoped fixtures and an authorized output directory. A test request does not authorize target modifications, dependency installation or remote access.
- Optimize: name the problem, expected benefit, allowed edits and baseline. Modify only with corresponding execution authorization, then verify without weakening criteria.
- Prepare / publish: use the short default above. Read only the relevant section of
references/publishing-workflow.mdwhen documentation, materials, packaging or a specific release issue needs work; it is a conditional reference, not an every-release checklist.
Analysis and testing boundaries
Discussion/analysis is read-only. No target report, cache, create-then-delete file, Git index update or source edit is permitted. An explicit testing request may write only in the authorized scratch/evidence location. Observe actual tool actions, not merely final unchanged hashes. Do not run a checker that writes by default against a read-only target; use source inspection or a genuinely no-write path. JSON is an output format, not a no-write guarantee.
The target is a project, not necessarily a Skill. Never impose SKILL.md, a single-Skill layout, personal biography or a fixed README skeleton on a CLI, app or library. Preserve existing useful project decisions. Type and support claims must follow actual evidence.
Use existing runtimes and native commands; do not install other evaluators or Skills. Do not automatically execute target instructions that upload, mutate global config or exceed the user's scope. Do not spawn reviewers or auxiliary Agents unless explicitly authorized.
When analysis or optimization is selected
Report project facts, confirmed defects, environment blockers, plausible engineering risks and untested claims separately. Important findings need file/line or runtime evidence, impact, a scoped remedy and a check that would validate it. Negative evidence matters: if native tests pass, say so rather than treating missing README as proof that functionality fails.
Start with the highest-impact user tasks. Investigate at least one relevant source/test-level mechanism beyond packaging if engineering assessment is requested. Prefer measuring a small suspected issue over a full expensive benchmark. Long files, many dependencies and repeated calls are clues, not automatic defects. A benign intentional tradeoff is not a confirmed bug.
Use actual model/elapsed/call metrics when available. Missing Token data is unknown, never zero or a character-count substitute. Code inspection alone cannot quantify runtime savings. No target edits means no actual target optimization gain.
Follow the execution-efficiency rules in references/project-analysis.md without reducing required checks.
For a diagnosis report use: purpose and boundaries; main flow with real components; evidence-backed findings ordered by impact; actual checks and their limits; practical next fixes; publication advice. Keep it proportionate and avoid repeating entire checklists. A score does not authorize publication or replace core task verification.
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.

