intent-layer
Set up hierarchical Intent Layer (AGENTS.md files) for codebases. Use when initializing a new project, adding context infrastructure to an existing repo, user asks to set up AGENTS.md, add intent layer, make agents understand the codebase, or scaffolding AI-friendly project documentation.
Install
npx skills add https://github.com/crafter-station/skills --skill intent-layerSKILL.md
Intent Layer
Hierarchical AGENTS.md infrastructure so agents navigate codebases like senior engineers.
Core Principle
Only ONE root context file. CLAUDE.md and AGENTS.md should NOT coexist at project root. Child AGENTS.md in subdirectories are encouraged for complex subsystems.
Workflow
1. Detect state
scripts/detect_state.sh /path/to/project
→ Returns: none | partial | complete
2. Route
none/partial → Initial setup (steps 3-5)
complete → Maintenance (step 6)
3. Measure [gate - show table first]
scripts/analyze_structure.sh /path/to/project
scripts/estimate_tokens.sh /path/to/each/source/dir
4. Decide
No root file → Ask: CLAUDE.md or AGENTS.md?
Has root file → Add Intent Layer section + child nodes if needed
5. Execute
Use references/templates.md for structure
Use references/node-examples.md for real-world patterns
Validate: one root, READ-FIRST directive, <4k tokens per node
6. Maintenance mode (when state=complete)
Ask user:
a) Audit nodes → Use references/capture-protocol.md for SME questions
b) Find candidates → Re-measure tokens, suggest new nodes
c) Both
When to Create Child Nodes
| Signal | Action |
|---|---|
| >20k tokens in directory | Create AGENTS.md |
| Responsibility shift | Create AGENTS.md |
| Hidden contracts/invariants | Document in nearest ancestor |
| Cross-cutting concern | Place at LCA |
Do NOT create for: every directory, simple utilities, test folders (unless complex).
Capture Questions
When documenting existing code, ask:
- What does this area own? What's out of scope?
- What invariants must never be violated?
- What repeatedly confuses new engineers?
- What patterns should always be followed?
Resources
Scripts:
scripts/detect_state.sh- Check Intent Layer state (none/partial/complete)scripts/analyze_structure.sh- Find semantic boundariesscripts/estimate_tokens.sh- Measure directory complexity
References:
references/templates.md- Root and child node templatesreferences/node-examples.md- Real-world examplesreferences/capture-protocol.md- SME interview protocol
Related skills
find-skillsvercel-labs3.6MHelps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.handoffmattpocock883KCompact the current conversation into a handoff document for another agent to pick up.microsoft-foundrymicrosoft618KBuild, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, create agent, update agent, add tool to agent, invoke agent, agent.yaml, agent insights, pull agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, prompt optimizer, optimize agcavemanjuliusbrussee544KUltra-compressed communication mode that cuts output tokens while keeping technical accuracy. Levels: lite, full, ultra and the wenyan variants. Use for /caveman, "caveman mode", "talk like caveman", "be brief" or "less tokens".
