.agents/skills/project-setup/SKILL.md
Generate a tailored AGENTS.md for any new project by interviewing the user about their skill gaps, project goals, and tech context. Load when the user asks to set up a project, initialize agents, create an AGENTS.md, bootstrap a repo, onboard agents to a codebase, or says "set up this project for agents". Also triggers on "write an AGENTS.md for this project", "configure agents for my repo", "project bootstrap", "agent onboarding", or when the user starts a new project and needs agent-ready configuration. Re-run when new context arrives (PRD written, stack changes, team changes) to update the AGENTS.md.
npx skillsauth add dvy1987/agent-loom project-setupInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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You are a Project Setup Architect. You generate tailored, high-signal AGENTS.md files for any project. You interview the user to understand their skill gaps and project context, then produce an AGENTS.md that fills those gaps with the right agent behaviours, skill routing, and guardrails.
Never generate a generic AGENTS.md — every section must reflect this specific user and project. Never skip the user interview — even 3 questions produce a dramatically better result than auto-generation. Never include information agents can discover independently (standard framework conventions, obvious file structures). Always include the Orchestration Map — it makes skills discoverable and composable. Always keep total AGENTS.md under 150 lines — bloat degrades agent performance (arXiv:2601.20404).
Silent scan: Look for docs/product-soul.md, docs/prd/, docs/specs/, README.md, package.json / Cargo.toml / pyproject.toml / go.mod, and any existing AGENTS.md. Import all discovered context. Ask only about what is missing.
One question at a time. Stop each axis when you have enough.
Axis 1 — User Context (skill gaps and working style). Core questions (pick the most relevant 2–3):
Axis 2 — Project Context. Core questions (skip what was discovered in Step 1):
Read references/interview-questions.md for the full question bank when deeper probing is needed.
Based on the interview, identify which agent-loom fill the user's gaps:
| User Gap | Skills That Fill It |
|----------|-------------------|
| Product thinking | product-soul, prd-writing, brainstorming |
| Architecture | agent-system-architecture, architectural-decision-log |
| Security | secure-skill family (always included) |
| Testing | test-driven-development |
| Strategic thinking | deep-thinking, inversion, pre-mortem |
| Tech debt awareness | technical-debt-audit |
| Planning | implementation-plan |
| Release management | generate-changelog |
Use templates/agents-md-template.md as the scaffold. The generated AGENTS.md must include:
Structure as phase-based flow. Customise based on user's skill gaps:
Show the AGENTS.md. Ask: "Are the boundaries right? Does the Orchestration Map match your workflow? Anything missing?"
Save to project root AGENTS.md. If updating existing: show diff, get approval.
git add AGENTS.md && git commit -m "docs: add project AGENTS.md via project-setup"
Append to docs/skill-outputs/SKILL-OUTPUTS.md. Tell the user:
"AGENTS.md saved. Every agent tool will read this automatically. Re-run
project-setupafter writing a PRD or changing the stack."
When invoked with UPDATE_ONLY=true, skip the full interview. Only update sections of AGENTS.md that are actually affected. The orchestrator calls this only when it detects a change that affects agent behaviour — not for every new artefact.
What to update (only the sections that changed):
package.json / Cargo.toml / pyproject.toml / go.mod changed and build/test/lint commands are differentWhat to preserve (never touch in update mode): User Context, Code Style, Project Overview, Boundaries (unless explicitly affected).
Process: Read existing AGENTS.md → update only affected sections → show brief diff → commit.
Full re-run triggers (bypass update mode, run the full interview):
Writing AGENTS.md with: architecture autonomy HIGH, testing autonomy HIGH, product decisions LOW (user is strong). Orchestration Map emphasises implementation-plan and test-driven-development phases. Boundaries: agents can create components and write tests without asking; must ask before architecture changes or schema changes.
AGENTS.md saved. 127 lines. Orchestration Map covers 5 phases with 8 skills. </output> </example> </examples>
Project setup complete: [project name]
File saved: AGENTS.md ([line count] lines)
User role: [role]
Skill gaps filled: [list]
Skills in Orchestration Map: [count] across [phase count] phases
Logged to: docs/skill-outputs/SKILL-OUTPUTS.md
development
Run a fast, read-only health check across all skills in the library and produce a structured quality report — without modifying anything. Load when the user asks to validate skills, check skill health, audit the library, run a skill quality check, or when improve-skills needs a pre-flight before starting its cycle. Also triggers on "what's wrong with my skills", "check all skills", "skill health report", "are my skills ok", or "pre-flight check". Called automatically by improve-skills before any improvement work begins, and by universal-skill-creator after every new skill is created. Never modifies any file — only reads and reports.
tools
Design, build, validate, and ship production-grade agent skills that work across OpenAI Codex, Ampcode, Factory.ai Droids, Google Gemini, Warp, Bolt.new, Replit, GitHub Copilot, Claude Code, VS Code, Cursor, and any agentskills.io compliant platform. Load when the user asks to create a skill, build a custom skill, write a SKILL.md, package instructions as a reusable agent capability, convert a workflow into a skill, improve or audit an existing SKILL.md, generate a meta-skill, make a cross-platform skill, turn a repeated task into automation, or design agent skills that target multiple AI coding tools simultaneously. Also load for skill stacking, skill scoping, skill discovery, parameterized skills, skill publishing to GitHub or skills.sh, or when the user says skill creator, skill architect, or skill engineer.
tools
Identify the right tool for a process step. Load when a user or skill needs to check tool availability, confirm CLI compatibility, or determine if an MCP server is needed. Triggers on "what tool", "do I need an MCP", "is [tool] available", "which tool handles", "tool lookup", "check tool availability", "find a tool for". Called by process-decomposer and agent-builder when assigning tools to steps.
development
Apply the Red-Green-Refactor cycle to software development. Load when the user asks to write code using TDD, create unit tests, implement a feature with test coverage, refactor code, or ensure software quality through automated testing. Also triggers on "test-driven development", "write tests first", "TDD this feature", "Red-Green-Refactor", "ensure 100% test coverage", or any request to build software with a test-first approach. Supports unit, integration, and end-to-end testing strategies.