issue
Skill1 starsChanged 10 days agoMITView on GitHub
Create GitHub issues with proper formatting, labels, and AI implementation prompts. Use when asked to create an issue, report a bug, or request a feature.
50 other projects use a version of this.
Adopted by
Most recently taken up by
- pch/rawmakasetheir own version, first seen Nov 8, 2026
- jmusick/skillstheir own version, first seen Nov 8, 2026
- dimsedra/skillstheir own version, first seen Nov 8, 2026
- fab-codes/agent-workflow-templatetheir own version, first seen Nov 8, 2026
- egregore-labs/egregoretheir own version, first seen Nov 6, 2026
- elastic/docs-buildertheir own version, first seen Nov 4, 2026
Used with
Projects with it also use browse, scout and 5 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
CodeWithBehnamSkillbrowse
Fast headless browser for QA testing and site dogfooding. Navigate any URL, interact with elements, verify page state, diff before/after actions, take annotated screenshots, check responsive layouts, test forms and uploads, handle dialogs, and assert element states. ~100ms per command. Use when you need to test a feature, verify a deployment, dogfood a user flow, or file a bug with evidence.
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lukeleekrSkillscout
GitHub 레포 스카우터. 내 Claude Code + Codex App 환경을 분석하여 필요한 GitHub 레포를 자동 추천하거나, 키워드로 GitHub을 검색합니다. "scout", "스카우트", "깃헙 탐방", "레포 추천", "repo search" 등의 키워드에 반응합니다.
Also in 3 projects that use this
sunnyclinches44Skillexplain
Explains code using real-world analogies and ASCII diagrams
Also in 4 projects that use this
VercelSkilldeploy
Deploy applications to Vercel. Use when the user says "deploy", "deploy to Vercel", "push to production", "deploy my app", or "go live".
Also in 4 projects that use this
kt057Skillcheck
lint, typecheck, test を一括実行して結果をサマリーする
Also in 3 projects that use this
Microsoft AzureSkillreflect
Learning capture system that extracts HIGH/MED/LOW confidence patterns from conversations to prevent repeating mistakes. Use after user corrections ("no", "wrong"), praise ("perfect", "exactly"), or when discovering edge cases. Complements .squad/agents/{agent}/history.md and .squad/decisions.md.
Also in 4 projects that use this
Other versions50 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 50
- remotion-dev/remotion★ 72ksame name
- tldraw/tldraw★ 51ksame name
- tokio-rs/toasty★ 3.3ksame name
- dataplat/dbatools★ 2.9ksame name
- pch/rawmakase★ 1.6ksame name
- aws/graph-explorer★ 490same name
- egregore-labs/egregore★ 293same name
- finos/git-proxy★ 263same name
- alamenai/terrae★ 245same name
- awslabs/loom★ 201same name
40 more not listed
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 repository41 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- analyze-codeSkill
- analyze-projectSkill
- analyze-testsSkill
- audit-mergesSkill
- babysit-prSkill
- backlogSkill
- branchSkill
- coderabbitSkill
- commitSkill
- greptileSkill
- implement-issuesSkill
- jiraSkill
- lintro-addSkill
- lintro-reviewSkill
- lintro-verifySkill
- lintSkill
- properizeSkill
- pr-raycastSkill
- prSkill
- raycastSkill
- rebaseSkill
- reconcileSkill
- scorecardSkill
- stand-ciSkill
- stand-generalSkill
- stand-odinSkill
- stand-pySkill
- stand-rustSkill
- stand-tsSkill
- sweep-prsSkill
- test-apiSkill
- test-shellSkill
- testSkill
- test-ui-qsfSkill
- test-uiSkill
- turbo-addSkill
- turbo-testSkill
- turbo-verifySkill
- which-prSkill
The file
We split this skill into the rules it gives an agent
8 rules. 0 are common, 6 are distinctive, and 2 are very specific to this project.
0
Common
Most of the 48 edited versions we read keep these.
6
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 8
Create well-structured GitHub issues following repository conventions.
- Distinctive: line 12
Use semantic prefixes matching conventional commits:
- Distinctive: line 136
When asked to create an issue:
- Distinctive: line 138
Gather requirements: - Ask clarifying questions if needed
- Very specific: line 139
Review existing issues: - Check for duplicates with gh issue list
- Distinctive: line 169
Comment before closing: Every closed issue gets a comment explaining _why_ it's closed and linking to whatever supersedes it (issue, PR, or …
- Very specific: line 172
Don't: gh issue close 42 with no comment.
- Distinctive: line 178
Repurpose before minting: When scope evolves, prefer retargeting an existing issue number over closing it and opening a new one — it …
“Common” is measured: kept by at least 6 in 10 of the 48 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
GitHub Issue Creation
Create well-structured GitHub issues following repository conventions.
Issue Title Format
Use semantic prefixes matching conventional commits:
feat(scope): short description # New feature
fix(scope): short description # Bug fix
docs(scope): short description # Documentation
chore(scope): short description # Maintenance
refactor(scope): short description # Code refactoring
perf(scope): short description # Performance improvementIssue Body Structure
For Feature Requests
## Summary
One paragraph describing the feature and its value.
## Problem
What problem does this solve? What's the current limitation?
## Proposed Solution
Detailed description with:
- Code examples showing desired behavior
- ASCII diagrams or mockups if applicable
- Configuration examples
## Implementation Notes
- Key files to modify
- Dependencies or prerequisites
- Potential challenges
## Benefits
- Bullet points of user/developer benefitsFor Bug Reports
## Summary
One paragraph describing the bug.
## Problem
What's happening vs what should happen?
Include:
- Steps to reproduce
- Error messages or screenshots
- Environment details if relevant
## Proposed Solution
How to fix it (if known).
## References
- Links to related issues, docs, or resourcesLabels
Apply appropriate labels based on issue type:
| Issue Type | Labels |
| New feature | enhancement |
| Bug fix | bug |
| Documentation | documentation |
| Security issue | bug, security |
| CI/CD related | ci |
| New tool (lintro) | enhancement, new tool |
AI Implementation Prompt
For issues that involve code changes, add a comment with an AI implementation prompt:
## AI Implementation Prompt
Use this prompt in a new agent session to implement this feature:
\```
[Concise implementation instructions including:]
## Requirements
### 1. [First Component]
- What to create/modify
- Code examples
### 2. [Second Component]
- What to create/modify
- Code examples
## Files to Modify
- `/path/to/file.py` - description of changes
## Tests
- Test requirements (pytest style, NO test classes)
- Use assertpy, fixtures
## Before Submitting
- Run `uv run lintro chk` - must pass
- Run `uv run lintro fmt` - must pass
- Run `uv run pytest` - must pass
\```Usage
When asked to create an issue:
- Gather requirements - Ask clarifying questions if needed
- Review existing issues - Check for duplicates with
gh issue list Create the issue:
gh issue create \ --title "feat(scope): description" \ --label "enhancement" \ --body "$(cat <<'EOF' ## Summary ... EOF )"Add AI prompt comment (for implementation issues):
gh issue comment <issue-number> --body "$(cat <<'EOF' ## AI Implementation Prompt ... EOF )"- Return the issue URL to the user
Backlog Stewardship
Rules for managing an existing backlog, not just creating new issues.
- Comment before closing. Every closed issue gets a comment explaining
why it's closed and linking to whatever supersedes it (issue, PR, or
commit).
- Don't:
gh issue close 42with no comment. - Do:
gh issue comment 42 --body "Superseded by #57, merged in a1b2c3d."thengh issue close 42.
- Don't:
- "Done" means merged to
main. Work that exists only on a branch is not done. Never close an issue because a branch has the fix — reopen or repurpose the issue instead until it lands onmain. - Repurpose before minting. When scope evolves, prefer retargeting an existing issue number over closing it and opening a new one — it preserves history and discussion.
- Placeholder convention for duplicates. For issues that are redundant or
would only duplicate another: prefer closing with a supersession comment
(see above) when the issue has useful comments, an implementation prompt,
or a useful body (repro steps, scoped feature spec, acceptance criteria)
— do not wipe history that other links or workflows may still need. Only
convert to a
placeholder(empty body, titleplaceholder, comments cleared) when the issue has no useful body and no useful discussion to preserve and you are explicitly reserving the number for reuse. - Never churn the backlog silently. Announce close/reopen/create/edit changes as you make them — the backlog should stay visible, not shift underneath readers.
- Keep content correct. Issues must carry accurate scope and follow the
/issueformat above. When an assessment (audit, review, incident) surfaces a real gap — bug, security issue, tech debt — add a spec-formatted, labeled issue for it rather than leaving it undocumented. - Dependency-update issues/PRs (Renovate, Dependabot): follow the
dependency-triage rule in the
stand-generalskill.
Examples
Good Issue Titles
feat(cli): add watch mode for continuous lintingfix(parser): handle empty input without crashingdocs(readme): add installation instructions for Windowsrefactor(core): simplify plugin loading logic
Bad Issue Titles
Add feature(no scope, not descriptive)Bug(not descriptive)Update code(vague, no scope)Fixed the thing(past tense, vague)
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.

