analyze-project
Skill1 starsChanged 10 days agoMITView on GitHub
High-level project analysis. Use when asked to analyze, review, or evaluate a project's architecture, structure, and overall health.
- Reads credentials
6 other projects use a version of this.
Adopted by
Most recently taken up by
- dmlguq456/heartingtheir own version, first seen Nov 8, 2026
- CsHeng/agent-skillstheir own version, first seen Nov 4, 2026
- jrjsmrtn/project-orchestration-skillstheir own version, first seen Nov 3, 2026
- hidekitux/skillstheir own version, first seen Sep 8, 2026
- Minitour/agentic-ontology-development-kittheir own version, first seen Jul 24, 2026
- lllllllama/RigorPilot-Skillstheir own version, first seen May 18, 2026
Other versions6 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 6
- lllllllama/RigorPilot-Skills★ 495same name
- jrjsmrtn/project-orchestration-skills★ 17same name
- dmlguq456/hearting★ 9same name
- CsHeng/agent-skills★ 3same name
- Minitour/agentic-ontology-development-kit★ 2same name
- hidekitux/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 repository41 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- analyze-codeSkill
- analyze-testsSkill
- audit-mergesSkill
- babysit-prSkill
- backlogSkill
- branchSkill
- coderabbitSkill
- commitSkill
- greptileSkill
- implement-issuesSkill
- issueSkill
- 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
9 rules. 0 are common, 8 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 6 edited versions we read keep these.
8
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 15
Verify catalog-like claims mechanically — if a claim implies "all N of X", script the check rather than eyeballing a sample.
- Distinctive: line 24
When asked to analyze project health:
- Distinctive: line 59
Verify lint, test, and deploy stages exist.
- Distinctive: line 86
Check for setup instructions, contribution guide, and documented public APIs.
- Distinctive: line 114
Look for deep cross-package imports, god modules, and circular import chains.
- Distinctive: line 118
Check the project against its own tracking, not just its code:
- Very specific: line 126
If gh is unavailable or unauthenticated, mark these GitHub-backed checks as "unverified" per the ground rules and continue the assessment.
- Distinctive: line 129
Check for: stale or conflicting open PRs.
- Distinctive: line 214
If starting this project today, what would you do differently?
“Common” is measured: kept by at least 6 in 10 of the 6 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
Project Analysis (Zoom Out)
Perform a high-level analysis of this project. Follow the procedural workflow below; use the rubric sections as reference when interpreting findings.
Ground rules
- Reproduce before reporting — read the actual files and run the tooling; never assert a finding based on file names, directory shapes, or vibes alone.
- Verify catalog-like claims mechanically — if a claim implies "all N of X", script the check rather than eyeballing a sample.
- Mark anything you couldn't verify as "unverified"; never guess or extrapolate.
- This is an assessment only: no code changes, no pushes, no triggering workflows or releases.
- Honor the target repo's standing context file when present (see step 0).
Usage
When asked to analyze project health:
0. Load repo context
At start, read the target repo's AGENTS.md and/or CLAUDE.md if present.
Precedence: AGENTS.md is authoritative when both exist — do not also
apply conflicting CLAUDE.md instructions; if only one exists, use that
file; if both conflict in a blocking way, stop and ask. Treat house
standards, operating agreement, and standing constraints in the chosen file
as binding for this assessment — including safety limits such as no paid
LLM API calls or local-only storage. See the stand-general skill's
Per-repo agent context section for the expected file shape. If neither
file exists, continue with chat instructions and stand-* skills only.
1. Map structure
Understand layout and entry points:
find . -maxdepth 3 -type f \( -name '*.py' -o -name '*.ts' -o -name '*.rs' -o -name 'Cargo.toml' -o -name 'package.json' -o -name 'pyproject.toml' \) | head -80
tree -L 3 -I 'node_modules|target|.venv|dist|build|__pycache__|.git' 2>/dev/null || find . -maxdepth 3 -type d | head -60Note: source roots, module boundaries, config locations, and test directories.
2. Check CI/CD
Inspect automation and pipeline coverage:
ls -la .github/workflows/ 2>/dev/null
rg -l 'lint|test|build|deploy' .github/workflows/
rg -n --hidden "uses:.*@[0-9a-f]{40}\b" .github/workflows || echo "No SHA-pinned actions found"Verify lint, test, and deploy stages exist; check for pinned action SHAs and reproducible
builds. Then go beyond presence: is CI validating what actually matters, or just
linting? Look for conditional skips (if: ... == '', path filters that silently
no-op a job) and for test suites that exist in the repo but never run in any
workflow — CI claiming a check happens is not the same as it executing.
3. Dependency health
Confirm lock files and manifest consistency:
ls -1 *lock* uv.lock bun.lockb Cargo.lock package-lock.json poetry.lock Pipfile.lock 2>/dev/null
rg -n 'version|dependencies' pyproject.toml package.json Cargo.toml | head -30Flag missing lock files, unpinned versions, or stale dependency patterns.
4. README and docs check
Assess onboarding and API documentation:
test -f README.md && head -80 README.md
find . -maxdepth 2 \( -name '*.md' -o -name 'docs' -type d \) | head -20
rg -l 'TODO|FIXME|TBD' README.md docs/Check for setup instructions, contribution guide, and documented public APIs.
5. Hardcoded config search
Find scattered or environment-specific values in source:
rg -n '(localhost|127\.0\.0\.1|0\.0\.0\.0|hardcoded|FIXME.*config)' --glob '!*.{lock,sum,md}'
rg -n '(API_URL|BASE_URL|DATABASE_URL)\s*=\s*["\x27]' --glob '!*.example' --glob '!*.env*'Evaluate against externalized configuration expectations.
6. Coupling and circular dependencies
Assess module boundaries (adapt to language):
# Python import graph (rough)
rg -n '^from |^import ' --type py | head -50
# TypeScript/JavaScript cross-imports
rg -n "^import .* from ['\"]\.\./" -t ts -t js | head -50
# Rust crate modules
rg -n '^mod |^pub mod ' -t rust | head -30Look for deep cross-package imports, god modules, and circular import chains.
7. Backlog, PR state, and release discipline
Check the project against its own tracking, not just its code:
gh pr list --state open
gh issue list --state open
gh pr list --state merged --limit 20If gh is unavailable or unauthenticated, mark these GitHub-backed checks as
"unverified" per the ground rules and continue the assessment.
Check for: stale or conflicting open PRs; issues claimed as done that are not actually
done in the code (verify by reading the code, not by trusting labels or comments);
merge history vs. stated milestones; lockfile version vs. manifest version drift;
CHANGELOG entries vs. git log; git tags vs. published releases.
8. Dead surface
Find things that look wired up but aren't — verify by reference, not by name:
- Workflows that silently skip themselves (conditional gates on paths/branches that never match)
- Scripts in the repo that no workflow, README, or Makefile ever calls
- Modules or components with zero references (
rgfor imports/usages of the symbol, not just its existence) - Stale committed artifacts (build output, generated files checked in as source)
- Orphaned docs/content unreachable from any nav, index, or README link
9. Product-quality scorecard
Build one row per area of the codebase — the full catalog, not a sample. Columns:
| Area | Correctness risk (low/med/high) | Test coverage (y/partial/none) | Consistency (ok/drifts) | Staleness / dead-code flags | Action |
Sort worst-first. Follow with the distribution across risk levels, the top 5-10 highest-risk areas, and any repo-wide patterns the scorecard reveals.
10. Rate and report findings
For each issue, assign severity:
- Critical — no CI, no lock files in production apps, secrets in repo, broken build
- Should Fix — poor docs, hardcoded config, unclear boundaries, missing tests in CI
- Nice to Have — naming inconsistencies, missing ADRs, UX polish
Output contract: lead with a TLDR verdict, then findings with file:line references,
then the scorecard and its summary, and end with one prioritized fix list ordered
by impact — not one list per section.
Full audit
For a complete audit rather than a zoom-out-only pass, follow this skill with analyze-code and analyze-tests, then merge all three sets of findings into the single prioritized fix list described above.
Reference — Architecture & Design
- Overall design quality and alignment with stated objectives
- Adherence to SOLID principles and separation of concerns
- Are layers (transport, business logic, data) clearly separated?
- API/interface design—are contracts clean, consistent, and hard to misuse?
- Code complexity—is it appropriately simple or over-engineered?
- Whether it reinvents solutions that existing libraries handle well
Reference — Maintainability
- How easily could a new developer onboard and contribute?
- Is the code self-documenting, or are complex sections unexplained?
- Consistent naming conventions and project structure
- Boundary clarity—are public vs internal APIs clearly delineated?
- Change impact—how localized is the blast radius of a typical change?
- Configuration management—is config externalized properly vs scattered/hardcoded?
Reference — CI/CD & DevOps
- Is the build reproducible?
- Are lint, test, and deploy pipelines in place?
- Are dependencies pinned and lock files committed?
Reference — Documentation
- README quality—does it cover setup, usage, and contribution?
- API documentation—are public interfaces documented?
- Architecture decision records (ADRs) or equivalent for key decisions
Reference — User Experience
- Interface design and usability
- Consistency of behavior and feedback
- Accessibility considerations
Reference — Retrospective
If starting this project today, what would you do differently?
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.

