Design, create, audit, and improve Claude Agent Skills with expert-level progressive disclosure. Use when building new skills, reviewing existing skills, debugging activation failures, encoding domain expertise, designing skills for subagent consumption, or understanding platform constraints and distribution surfaces. NOT for general Claude Code features, runtime debugging, non-skill coding, or MCP server implementation.
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SKILL.md
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name
skill-architect
description
Design, create, audit, and improve Claude Agent Skills with expert-level progressive disclosure. Use when building new skills, reviewing existing skills, debugging activation failures, encoding domain expertise, designing skills for subagent consumption, or understanding platform constraints and distribution surfaces. NOT for general Claude Code features, runtime debugging, non-skill coding, or MCP server implementation.
{"category":"Productivity & Meta","tags":["architect","create-skill","improve-skill","skill-audit"],"pairs-with":[{"skill":"skill-creator","reason":"The architect designs skill structure; the creator guides implementation following those patterns"},{"skill":"skill-grader","reason":"Grading feedback identifies architectural weaknesses that the architect addresses"},{"skill":"skill-documentarian","reason":"Documentation standards complement architectural design for complete skill delivery"}]}
Skill Architect: The Authoritative Meta-Skill
The unified authority for creating expert-level Agent Skills. Encodes the knowledge that separates a skill that merely exists from one that activates precisely, teaches efficiently, and makes users productive immediately.
Philosophy
Great skills are progressive disclosure machines. They encode real domain expertise (shibboleths), not surface instructions. They follow a three-layer architecture: lightweight metadata for discovery, lean SKILL.md for core process, and reference files for deep dives loaded only on demand.
When to Use This Skill
Creating new skills from scratch or from existing expertise
Auditing/reviewing skills for quality, activation, and progressive disclosure
Improving activation rates and reducing false positives
Designing skills that subagents consume effectively
Building self-contained tools (scripts, MCPs, subagents)
Debugging why skills don't activate or activate incorrectly
NOT for: General Claude Code features (slash commands, MCP server implementation), non-skill coding advice or code review, debugging runtime errors (use domain-specific skills), template generation without real domain expertise to encode.
Quick Wins (Immediate Improvements)
For existing skills, apply in priority order:
Tighten description -- Follow [What] [When to use]. NOT for [Exclusions] formula
Check line count -- SKILL.md must be <500 lines; move depth to /references
Add NOT clause -- Prevent false activation with explicit exclusions
Add 1-2 anti-patterns -- Use shibboleth template (Novice/Expert/Timeline)
Remove dead files -- Delete unreferenced files in scripts/ and references/ (no phantoms)
Test activation -- Write 5 queries that should trigger and 5 that shouldn't
Progressive Disclosure Architecture
Skills use three-layer loading. The runtime scans metadata at startup, loads SKILL.md on activation, and pulls reference files only when the agent decides it needs them.
Layer
Content
Size
Loading
1. Metadata
name + description in frontmatter
~100 tokens
Always in context (catalog scan)
2. SKILL.md
Core process, decision trees, brief anti-patterns
<5k tokens
On skill activation
3. References
Deep dives, examples, templates, specs
Unlimited
On-demand, per-file, only when relevant
Critical rules:
Keep SKILL.md under 500 lines. Move depth to /references.
Reference files are NOT auto-loaded. Only SKILL.md enters context on activation.
In SKILL.md, list each reference file with a 1-line description of when to consult it.
Never instruct "read all reference files before starting." Instead: "Read only the files relevant to the current step."
Frontmatter Rules
Required Fields
Key
Purpose
Constraints
name
Lowercase-hyphenated identifier
Max 64 chars, a-z/0-9/hyphens only, no "anthropic" or "claude", no XML tags
description
Activation trigger: [What] [When to use]. NOT for [Exclusions]
Max 1024 chars, no XML tags. See Description Formula
Optional Fields
Key
Purpose
Example
allowed-tools
Comma-separated tool names (least privilege)
Read,Write,Grep
argument-hint
Hint shown in autocomplete for expected arguments
"[path] [format]"
license
License identifier
MIT
disable-model-invocation
If true, only user-triggered via /skill-name
true
user-invocable
Controls whether skill appears in UI menus
true
context
Execution context; fork runs skill in isolated subagent
fork
agent
Which subagent type when context: fork
code-reviewer
model
Override model when skill is active
sonnet
hooks
Hooks scoped to this skill's lifecycle
See hooks reference
metadata
Arbitrary key-value map for tooling/dashboards
author: your-org
Custom Keys (Safe to Use)
Custom keys like category, tags, version are ignored by Claude Code but safe to include for your own tooling (gallery websites, documentation generators, dashboards). Place them inside the metadata: block to keep them organized and avoid confusion with real runtime keys.
Invalid Keys (Confusingly Similar to Valid Ones)
# These look like valid keys but aren't -- use the correct alternativestools:Read,Write# Use 'allowed-tools' insteadintegrates_with: [...] # Use SKILL.md body text insteadoutputs: [...] # Use SKILL.md Output Format section insteaddependencies: [...] # Use SKILL.md body text (not a real frontmatter key)bundled-resources: [...] # Use SKILL.md body text (not a real frontmatter key)
Common mistakes that prevent loading: tools: instead of allowed-tools: (silently ignored), YAML list syntax [Read, Write] in allowed-tools (use comma-separated string), name with spaces/uppercase (use lowercase-hyphenated), name not matching directory name (causes activation mismatch). Run python scripts/validate_skill.py <path> to catch all of these.
Platform constraints (name: 64 chars, description: 1024 chars, upload: 8MB, 8 skills/request max, no XML tags): See references/claude-extension-taxonomy.md for full details. Skills do NOT sync across Claude.ai, Claude API, and Claude Code -- maintain Git as single source of truth.
Description Formula
Pattern: [What it does] [When to use -- be slightly pushy]. NOT for [Exclusions].
The description is the most important line for activation. Claude's runtime scans descriptions to decide which skill to load. Claude evaluates descriptions semantically, not via keyword matching. It reasons about whether your description covers the user's intent. Claude also tends to undertrigger -- make descriptions slightly pushy to combat this.
Problem
Bad
Good
Too vague
"Helps with images"
"CLIP semantic search for image-text matching and zero-shot classification. NOT for counting, spatial reasoning, or generation."
No exclusions
"Reviews code changes"
"Reviews TypeScript/React diffs and PRs for correctness. NOT for writing new features."
Catch-all
"Helps with product management"
"Writes and refines product requirement documents (PRDs). NOT for strategy decks."
Full guide with more examples: See references/description-guide.md
SKILL.md Template
---
name: your-skill-name
description: [What it does] [When to use -- be slightly pushy]. NOT for [Exclusions].
allowed-tools: Read,Write
---# Skill Name
[One sentence purpose]
## When to Use
Use for: [A, B, C with specific trigger keywords]
NOT for: [D, E, F -- explicit boundaries]
## Core Process
[Mermaid diagrams for decisions/flows. See visual-artifacts.md for catalog]
## Anti-Patterns### [Pattern Name]**Novice**: [Wrong assumption]
**Expert**: [Why it's wrong + correct approach]
**Timeline**: [When this changed, if temporal]
## References-`references/guide.md` -- Consult when [specific situation]
-`references/examples.md` -- Consult for [worked examples of X]
After real-world use: notice struggles, improve SKILL.md and resources, update CHANGELOG.md.
Designing Skills for Subagent Consumption
Three Skill-Loading Layers
Preloaded (2-5 core skills): Injected into the subagent's system context.
Dynamically selected: Subagent receives a catalog (name + 1-line description) and picks 1-3 matching skills.
Execution-time: Subagent reads each skill's "When to use" section, follows numbered steps, respects output contracts, runs QA checks.
Subagent Prompt Structure
Four sections: Identity (narrow role), Skill usage rules (skills as standard operating procedures), Task loop (restate, select skills, plan, execute, validate, return), Constraints (quality bar, safety, tie-breaking).
Full templates and orchestration patterns: See references/subagent-design.md
Visual Artifacts: Mermaid Diagrams
For humans, diagrams render as visual flowcharts, state machines, and timelines. For agents, Mermaid is a text-based graph DSL -- A -->|Yes| B is an explicit, unambiguous edge. Both audiences benefit.
Rule: If a skill describes a process, decision tree, architecture, state machine, or data relationship, include a Mermaid diagram.
Skill Content
Diagram Type
Syntax
Decision trees / troubleshooting
Flowchart
flowchart TD
API/agent communication protocols
Sequence
sequenceDiagram
Lifecycle / status transitions
State
stateDiagram-v2
Temporal knowledge / evolution
Timeline
timeline
Data models / schemas
ER
erDiagram
Domain taxonomy / concept maps
Mindmap
mindmap
Priority matrices (2-axis)
Quadrant
quadrantChart
Infrastructure / cloud topology
Architecture
architecture-beta
Full catalog (all 23 types) with syntax, examples, and YAML config: See references/visual-artifacts.md
Encoding Shibboleths
Expert knowledge that separates novices from experts. Things LLMs get wrong due to outdated training data or cargo-culted patterns.
Shibboleth Template
### Anti-Pattern: [Name]**Novice**: "[Wrong assumption]"
**Expert**: [Why it's wrong, with evidence]
**Timeline**: [Date]: [Old way] -> [Date]: [New way]
**LLM mistake**: [Why LLMs suggest the old pattern]
**Detection**: [How to spot this in code/config]
Full catalog with case studies: See references/antipatterns.md
Self-Contained Tools and the Extension Taxonomy
Skills are one of seven Claude extension types. Most skills should include scripts. MCPs are only for auth/state boundaries. Plugins are for sharing skills across teams/community.
Need
Extension Type
Key Requirement
Domain expertise / process
Skill (SKILL.md)
Decision trees, anti-patterns, output contracts
Packaging & distribution
Plugin (plugin.json)
Bundles skills + hooks + MCP + agents
External API + auth
MCP Server
Working server + setup README
Repeatable local operation
Script
Actually runs (not a template), minimal deps
Multi-step orchestration
Subagent
4-section prompt, skills, workflow
User-triggered action
Slash Command
Skill with user-invocable: true
Lifecycle automation
Hook
17+ events: PreToolUse, PostToolUse, Stop, etc.
Programmatic access
Agent SDK
npm/pip package, CI/CD pipelines
Full taxonomy with examples and common mistakes: See references/claude-extension-taxonomy.mdDetailed tool patterns: See references/self-contained-tools.mdPlugin creation and distribution: See references/plugin-architecture.md
Tool Permissions (Least Privilege)
Access Level
allowed-tools
Read-only
Read,Grep,Glob
File modifier
Read,Write,Edit
Build integration
Read,Write,Bash(npm:*,git:*)
Never for untrusted
Unrestricted Bash
Anti-Pattern Summary
#
Anti-Pattern
Fix
1
Documentation Dump
Decision trees in SKILL.md, depth in /references
2
Missing NOT clause
Always include "NOT for X, Y, Z" in description
3
Phantom Tools
Only reference files that exist and work
4
Template Soup
Ship working code or nothing
5
Overly Permissive Tools
Least privilege: specific tool list, scoped Bash
6
Stale Temporal Knowledge
Date all advice, update quarterly
7
Catch-All Skill
Split by expertise type, not domain
8
Vague Description
Use [What] [When to use]. NOT for [Exclusions]
9
Eager Loading
Never "read all files first"; lazy-load references
10
Prose-Only Processes
Use Mermaid diagrams for decisions, workflows, architectures
Full case studies: See references/antipatterns.md
Validation Checklist
[ ] SKILL.md exists and is <500 lines
[ ] Frontmatter has name + description (minimum required)
[ ] Description follows [What][When to use] NOT [Exclusions] formula
[ ] Description is specific and context-rich (semantic activation, not keyword lists)
[ ] Name and description are aligned (not contradictory)
[ ] At least 1 anti-pattern with shibboleth template
[ ] All referenced files actually exist (no phantoms)
[ ] Scripts work (not templates), have clear CLI, handle errors
[ ] Reference files each have a 1-line purpose in SKILL.md
[ ] Processes/decisions/lifecycles use Mermaid diagrams, not prose
[ ] CHANGELOG.md tracks version history
[ ] If subagent-consumed: output contracts are defined
[ ] Skill passes its own validation tools (meta-consistency)
Run automated checks: python scripts/validate_skill.py <path> and python scripts/validate_mermaid.py <path>
Success Metrics
Metric
Target
Correct activation
>90%
False positive rate
<5%
Token usage
<5k tokens
Time to productive
<5 min
Reference Files
Consult these for deep dives -- they are NOT loaded by default:
File
Consult When
references/knowledge-engineering.md
KE methods for extracting expert knowledge into skills
references/description-guide.md
Writing or rewriting a skill description
references/antipatterns.md
Looking for shibboleths, case studies, or temporal patterns
references/self-contained-tools.md
Adding scripts, MCP servers, or subagents to a skill
references/subagent-design.md
Designing skills for subagent consumption or orchestration
references/claude-extension-taxonomy.md
Skills vs Plugins vs MCPs vs Hooks vs Agent SDK
references/plugin-architecture.md
Creating, packaging, and distributing plugins
references/visual-artifacts.md
Adding Mermaid diagrams: all 23 types, YAML config
references/mcp-template.md
Building an MCP server for a skill
references/subagent-template.md
Defining subagent prompts and multi-agent pipelines
