agentleFS
RajeshKalidandiRajeshKalidandi/dotclaude/skills/project-autopilot/SKILL.md

project-autopilot

Skill1 starsChanged 7 months agoMITView on GitHub

Auto-detect project type, scaffold CLAUDE.md and memory on first session. Use at the start of every session in a project directory.

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3 other projects use a version of this.

Adopted by

Most recently taken up by

  • Other versions3 projects use a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 3

    1. diiiiiiylan/project-autopilot★ 1same name
    2. mmetwally-dev/project-autopilot★ 1same name
    3. SubliminalCoding/bilbroswagginz-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 repositoryOne other file it gives its agents.

The file

Show its rules and text

We split this skill into the rules it gives an agent

15 rules. 0 are common, 10 are distinctive, and 5 are very specific to this project.

  • 0

    Common

    Most of the 3 edited versions we read keep these.

  • 10

    Distinctive

    This author's own choices. Worth a look.

  • 5

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    When the project is missing CLAUDE.md or project memory

    line 13
  2. Distinctive:

    When switching to a project you haven't touched recently

    line 14
  3. Distinctive:

    After cloning a new repo

    line 15
  4. Distinctive:

    Check these in parallel:

    line 19
  5. Distinctive:

    Every field must come from READING actual files.

    line 80
  6. Distinctive:

    If a field can't be determined, omit it.

    line 81
  7. Very specific:

    Run cat package.json | jq '.scripts' to get real commands.

    line 82
  8. Very specific:

    Run ls -la at key directories to map structure.

    line 83
  9. Distinctive:

    Read 2-3 source files to detect conventions (naming, imports, patterns).

    line 84
  10. Very specific:

    Create project memory at ~/.claude/projects/{project-path}/memory/:

    line 88
  11. Very specific:

    After scaffolding, check global memory at ~/.claude/projects/-Users-{username}/memory/ for:

    line 127
  12. Distinctive:

    Never block the user: If they give a task immediately, do the scan in background or weave it into the first task.

    line 134
  13. Distinctive:

    Never fabricate: Every claim in CLAUDE.md must trace to an actual file.

    line 135
  14. Distinctive:

    Update, don't duplicate: If files exist but are stale, update them.

    line 137
  15. Very specific:

    Parallel everything: Use parallel tool calls to scan package.json, README, directory structure, and recent git history simultaneously.

    line 138

“Common” is measured: kept by at least 6 in 10 of the 3 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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Project Autopilot

Intelligent project onboarding that runs on session start. Detects the project, scaffolds context files, and gets you productive in seconds.

When to Use

  • Every session start in a project directory
  • When the project is missing CLAUDE.md or project memory
  • When switching to a project you haven't touched recently
  • After cloning a new repo

Phase 1: Detect Project State

Check these in parallel:

1. Does {project_root}/CLAUDE.md exist?
2. Does ~/.claude/projects/{project-path}/memory/MEMORY.md exist?
3. What's the tech stack? (scan for package.json, requirements.txt, Cargo.toml, go.mod, Gemfile, pyproject.toml, composer.json, Makefile, Dockerfile)
4. Is this a monorepo? (check for workspaces in package.json, turborepo.json, pnpm-workspace.yaml, nx.json)
5. What framework? (next.config.*, nuxt.config.*, svelte.config.*, astro.config.*, vite.config.*)
6. What database? (prisma/, drizzle.config.*, supabase/, .env* for DATABASE_URL)
7. What CI/CD? (.github/workflows/, vercel.json, vercel.ts, netlify.toml, Dockerfile)
8. Git state? (git log --oneline -5, current branch, remote)

Phase 2: Scaffold CLAUDE.md (if missing)

Generate a project-level CLAUDE.md by READING the actual codebase. Never guess.

Structure:

# {Project Name}

{One-line description derived from README or package.json}

## Tech Stack
- Runtime: {node/python/rust/go + version from .tool-versions, .nvmrc, package.json engines}
- Framework: {next/nuxt/svelte/express/fastapi/etc + version}
- Database: {postgres/supabase/sqlite/mongo + ORM}
- Hosting: {vercel/aws/railway/fly + evidence}
- Key deps: {list top 5-8 non-obvious dependencies}

## Commands
- Dev: `{actual dev command from package.json scripts or Makefile}`
- Build: `{actual build command}`
- Test: `{actual test command}`
- Lint: `{actual lint command}`
- Deploy: `{actual deploy command if discoverable}`
- DB migrate: `{actual migration command if applicable}`

## Architecture
- {Map the top-level directory structure}
- {Identify the routing pattern: file-based, explicit, etc}
- {Identify the data flow: API routes -> services -> DB, or direct, etc}
- {Note any patterns: repository pattern, service layer, etc}

## Conventions (derived from existing code)
- {Naming patterns observed in the codebase}
- {Import style: absolute vs relative, barrel exports}
- {State management approach if frontend}
- {Error handling patterns}
- {Testing patterns if tests exist}

## Key Files
- Entry point: `{path}`
- Config: `{path}`
- Routes/API: `{path}`
- Database schema: `{path}`
- Environment: `{.env.example or .env.local path}`

IMPORTANT:

  • Every field must come from READING actual files. Never fabricate.
  • If a field can't be determined, omit it. Don't write "unknown."
  • Run cat package.json | jq '.scripts' to get real commands.
  • Run ls -la at key directories to map structure.
  • Read 2-3 source files to detect conventions (naming, imports, patterns).

Phase 3: Scaffold Memory (if missing)

Create project memory at ~/.claude/projects/{project-path}/memory/:

MEMORY.md (index)

- [Project Overview](project_overview.md) -- tech stack, purpose, architecture summary
- [Architecture](project_architecture.md) -- key patterns, data flow, component structure

project_overview.md

---
name: project_overview
description: {Project name} -- {one-line summary of what it does and key tech}
type: project
---

{2-3 sentences: what it is, who it's for, current state}

**Tech stack:** {framework + db + hosting}
**Repo:** {remote URL if available}
**Status:** {active/maintenance/new based on recent commit activity}

project_architecture.md

---
name: project_architecture
description: Architecture patterns and key decisions for {project name}
type: project
---

{Key architectural patterns observed}

**Why:** {Inferred from code structure}
**How to apply:** {When making changes, follow these patterns}

Phase 4: Cross-Pollinate

After scaffolding, check global memory at ~/.claude/projects/-Users-{username}/memory/ for:

  • Similar tech stacks in other projects — reuse known patterns
  • Debugging patterns that apply across projects
  • User preferences that should carry over

Rules

  1. Never block the user. If they give a task immediately, do the scan in background or weave it into the first task.
  2. Never fabricate. Every claim in CLAUDE.md must trace to an actual file.
  3. Keep it lean. CLAUDE.md should be <100 lines. Memory files should be <50 lines each.
  4. Update, don't duplicate. If files exist but are stale, update them. Don't create new ones.
  5. Parallel everything. Use parallel tool calls to scan package.json, README, directory structure, and recent git history simultaneously.

Quick Reference: Stack Detection

FileSignals
package.jsonNode.js, framework (next/nuxt/svelte), scripts, deps
next.config.*Next.js + version
tsconfig.jsonTypeScript + strictness level
prisma/schema.prismaPrisma ORM + database type
drizzle.config.*Drizzle ORM
supabase/ or .env*SUPABASE*Supabase
vercel.json or vercel.tsVercel hosting
.github/workflows/GitHub Actions CI
DockerfileContainerized deployment
tailwind.config.*Tailwind CSS
requirements.txt / pyproject.tomlPython project
Cargo.tomlRust project
go.modGo project
turbo.json / pnpm-workspace.yamlMonorepo

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