analyze
Skill2 starsChanged 8 months agoMITView on GitHub
Analyze a project's codebase, PR review patterns, and conventions. Run this first before creating agents. Outputs a structured analysis that create-team uses.
70 other projects use a version of this.
Adopted by
Most recently taken up by
- ansvisor/ansvisortheir own version, first seen Nov 8, 2026
- ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tooltheir own version, first seen Nov 8, 2026
- nisarth/claude-skills-storetheir own version, first seen Nov 8, 2026
- jhlee0409/proc-janitortheir own version, first seen Nov 8, 2026
- Beskars-Code/Skillstheir own version, first seen Nov 6, 2026
- Gabriel-Lafrance/Skillstheir own version, first seen Nov 6, 2026
Used with
Projects with it also use constitution, revise and 10 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.
ArvorCoSkillconstitution
Create or update the project constitution - personalized governance and coding principles. Use when starting a project or updating project standards. Triggers on: create constitution, update principles, set project rules.
Also in 4 projects that use this
stormlightlabsSkillrevise
Address review comments on an open pull request and push the fixes. Use for /edit, /revise, or when asked to respond to review feedback on a PR number.
Also in 3 projects that use this
DockerSkillwrite
Write or edit reader-facing technical prose for immediate comprehension. Use for documentation, PR titles and descriptions, release notes, design documents, user-facing explanations, and substantive comments. Also use when asked to make writing clearer, more natural, less AI-generated, or easier to read. For documentation fixes, handles edits, formatting, self-review, and commits after research identifies what to change. Do not use for code-only tasks with no prose deliverable.
Also in 6 projects that use this
ArvorCoSkillspecify
Create feature specification from natural language description. Use when starting a new feature or creating a spec. Triggers on: create spec, specify feature, new feature spec.
Also in 5 projects that use this
H-mmerSkillsubmit
Draft and submit a vulnerability report to the bug bounty platform. Reads scope.yaml for platform/program, uses brain + findings for content. Always drafts first for review.
Also in 3 projects that use this
GoogleSkillquality
Evaluates whether a GitHub issue is spam, empty, needs more information, or is OK to proceed.
Also in 3 projects that use this
- +1 more from ArvorCo
Other versions70 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 70
- anthropics/knowledge-work-plugins★ 35ksame name
- Yeachan-Heo/oh-my-codex★ 34ksame name
- oxsecurity/megalinter★ 2.6ksame name
- H-mmer/pentest-agents★ 815same name
- ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool★ 432same name
- hardisgroupcom/sfdx-hardis★ 432same name
- nwiizo/tfmcp★ 373same name
- hsantanna88/clo-author★ 262same name
- hugosantanna/clo-author★ 262same name
- ansvisor/ansvisor★ 233same name
60 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 repository2 other files it gives its agents.
- challengeSkill
- create-teamSkill
The file
We split this skill into the rules it gives an agent
5 rules. 0 are common, 4 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 60 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 11
Read these files if they exist:
- Distinctive: line 22
Test framework, assertion library, coverage requirements
- Distinctive: line 28
Read 5-10 key source files for patterns
- Distinctive: line 29
Read 5-10 test files for testing conventions
- Very specific: line 60
Read everything in .context/ if it exists.
“Common” is measured: kept by at least 6 in 10 of the 60 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
Analyze the current project to prepare for agent team creation. Read everything relevant and produce a structured analysis.
Step 1: Project Foundation
Read these files if they exist:
- README.md, CONTRIBUTING.md, CHANGELOG.md
- .github/pull_request_template.md
- .github/ISSUE_TEMPLATE/
Step 2: Tech Stack
Identify:
- Language and version (go.mod, package.json, Cargo.toml, pyproject.toml, etc.)
- Build system and commands
- Linter config with exact rules
- Test framework, assertion library, coverage requirements
- CI/CD workflows (.github/workflows/)
Step 3: Code Patterns
- Map directory structure with Glob
- Read 5-10 key source files for patterns
- Read 5-10 test files for testing conventions
- Identify the extension/plugin/registration pattern (how new features are added)
Step 4: PR Review Analysis
Find the lead reviewer:
gh pr list --state all --limit 100 --json number,reviews --jq '.[].reviews[].author.login' 2>/dev/null | sort | uniq -c | sort -rn | head -5Find external contributor PRs:
gh pr list --state all --limit 200 --json number,title,state,author --jq '.[] | "\(.number) [\(.state)] \(.author.login): \(.title)"' 2>/dev/nullFor each external PR with lead reviewer feedback, extract BOTH:
PR-level reviews:
gh api repos/OWNER/REPO/pulls/NUMBER/reviews --jq '.[] | select(.user.login == "REVIEWER") | .body' 2>/dev/nullInline code comments:
gh api repos/OWNER/REPO/pulls/NUMBER/comments --jq '.[] | select(.user.login == "REVIEWER") | "FILE: \(.path):\(.line // .original_line)\nCOMMENT: \(.body[:400])"' 2>/dev/nullAnalyze at least 15-20 PRs. Rank reviewer patterns by frequency into tiers.
Step 5: Context Folder
Read everything in .context/ if it exists.
Output
Save the analysis to .context/forge-analysis.md with these sections:
# Forge Analysis: [Project Name]
## Tech Stack
[language, build, linter, test framework, CI]
## Code Patterns
[file structure, naming conventions, registration pattern]
## Test Conventions
[package naming, assertion library, fixture patterns, coverage requirement]
## PR Review Patterns
### Lead Reviewer: [name]
### Tier 1 (50%+ of PRs)
[patterns with exact quotes]
### Tier 2 (25-50%)
[patterns with exact quotes]
### Tier 3 (10-25%)
[patterns with exact quotes]
### Things NOT to Flag
[verified false positives]
## PR Format
[title format, body structure, checklist]
## Contribution Type
[what external contributors typically add]
## Build/Generate Commands
[commands that must run before submitting]Tell the user the analysis is complete and they can run /claude-army:create-team next.
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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.

