| name | writing-skills |
| description | Use when creating new skills, editing existing skills, or verifying skill guidance before rollout, and need repeatable patterns for authoring and validating reusable skills. |
Writing Skills
Overview
Writing skills IS Test-Driven Development applied to process documentation.
In this repository, skill assets live under .agents/skills/.
Current Android Repo Overrides
When using this skill inside the current Android repository, follow these local overrides first:
- Repo-local conventions live in
AGENTS.md, not CLAUDE.md
- Repo-local skill paths use
.agents/skills/
SKILL.md frontmatter description must explain both what the skill does and when to use it, while keeping triggering conditions explicit- If an external authoring recommendation conflicts with repo-local workflow or asset structure, prefer the repo-local rule
You write test cases (pressure scenarios with subagents), watch them fail (baseline behavior), write the skill (documentation), watch tests pass (agents comply), and refactor (close loopholes).
Core principle: If you didn't watch an agent fail without the skill, you don't know if the skill teaches the right thing.
Background note: This skill uses RED-GREEN-REFACTOR as a mental model for documentation work. Do not assume any external prerequisite skill is available; when repo-local workflow rules exist, follow those first.
Official guidance: For Anthropic's official skill authoring best practices, see anthropic-best-practices.md. This document provides additional patterns and guidelines that complement the TDD-focused approach in this skill.
What is a Skill?
A skill is a reference guide for proven techniques, patterns, or tools. Skills help future Claude instances find and apply effective approaches.
Skills are: Reusable techniques, patterns, tools, reference guides
Skills are NOT: Narratives about how you solved a problem once
TDD Mapping for Skills
| TDD Concept | Skill Creation |
|---|
| Test case | Pressure scenario with subagent |
| Production code | Skill document (SKILL.md) |
| Test fails (RED) | Agent violates rule without skill (baseline) |
| Test passes (GREEN) | Agent complies with skill present |
| Refactor | Close loopholes while maintaining compliance |
| Write test first | Run baseline scenario BEFORE writing skill |
| Watch it fail | Document exact rationalizations agent uses |
| Minimal code | Write skill addressing those specific violations |
| Watch it pass | Verify agent now complies |
| Refactor cycle | Find new rationalizations → plug → re-verify |
The entire skill creation process follows RED-GREEN-REFACTOR.
When to Create a Skill
Create when:
- Technique wasn't intuitively obvious to you
- You'd reference this again across projects
- Pattern applies broadly (not project-specific)
- Others would benefit
Don't create for:
- One-off solutions
- Standard practices well-documented elsewhere
- Project-specific repo conventions (put in the repo's local governance file; in this repository,
AGENTS.md)
- Mechanical constraints (if it's enforceable with regex/validation, automate it—save documentation for judgment calls)
Skill Types
Technique
Concrete method with steps to follow (condition-based-waiting, root-cause-tracing)
Pattern
Way of thinking about problems (flatten-with-flags, test-invariants)
Reference
API docs, syntax guides, tool documentation (office docs)
Directory Structure
.agents/skills/
skill-name/
SKILL.md # Main reference (required)
supporting-file.* # Only if needed
Flat namespace - all skills in one searchable namespace
Separate files for:
- Heavy reference (100+ lines) - API docs, comprehensive syntax
- Reusable tools - Scripts, utilities, templates
Keep inline:
- Principles and concepts
- Code patterns (< 50 lines)
- Everything else
SKILL.md Structure
Frontmatter (YAML):
- Two required fields:
name and description (see agentskills.io/specification for all supported fields)
- Max 1024 characters total
name: Use letters, numbers, and hyphens only (no parentheses, special chars)description: Third-person; in this repository it should explain both what the skill does and when to use it
- Start with "Use when..." to make triggering conditions explicit
- Include a short statement of what the skill helps with when the repo requires it
- Include specific symptoms, situations, and contexts
- Avoid over-summarizing the full workflow in metadata; keep detailed process in the body
- Keep under 500 characters if possible
---
name: Skill-Name-With-Hyphens
description: Use when [specific triggering conditions and symptoms], and need [what the skill helps accomplish]
---
# Skill Name
## Overview
What is this? Core principle in 1-2 sentences.
## When to Use
[Small inline flowchart IF decision non-obvious]
Bullet list with SYMPTOMS and use cases
When NOT to use
## Core Pattern (for techniques/patterns)
Before/after code comparison
## Quick Reference
Table or bullets for scanning common operations
## Implementation
Inline code for simple patterns
Link to file for heavy reference or reusable tools
## Common Mistakes
What goes wrong + fixes
## Real-World Impact (optional)
Concrete results
Claude Search Optimization (CSO)
Critical for discovery: Future Claude needs to FIND your skill
1. Rich Description Field
Purpose: Claude reads description to decide which skills to load for a given task. Make it answer: "Should I read this skill right now?"
Format: Start with "Use when..." to focus on triggering conditions
CRITICAL: In generic ecosystems, description may focus mostly on triggering conditions. In this repository, follow repo-local rules first: description must still make triggering conditions explicit, but it should also identify what the skill helps accomplish.
Do not summarize the entire skill workflow in the description. Keep the detailed process in the skill body.
Why this matters: Testing revealed that when a description summarizes the skill's workflow, Claude may follow the description instead of reading the full skill content. A description saying "code review between tasks" caused Claude to do ONE review, even though the skill's flowchart clearly showed TWO reviews (spec compliance then code quality).
When the description was changed to "Use when executing implementation plans with independent tasks, and need disciplined plan execution in the current session" (no workflow summary), Claude correctly read the flowchart and followed the two-stage review process.
The trap: Descriptions that summarize workflow create a shortcut Claude will take. The skill body becomes documentation Claude skips.
description: Use when executing plans - dispatches subagent per task with code review between tasks
description: Use for TDD - write test first, watch it fail, write minimal code, refactor
description: Use when executing implementation plans with independent tasks, and need disciplined plan execution in the current session
description: Use when implementing any feature or bugfix, and need a repeatable approach before writing implementation code
Content:
- Use concrete triggers, symptoms, and situations that signal this skill applies
- Describe the problem (race conditions, inconsistent behavior) not language-specific symptoms (setTimeout, sleep)
- Keep triggers technology-agnostic unless the skill itself is technology-specific
- If skill is technology-specific, make that explicit in the trigger
- Write in third person (injected into system prompt)
- NEVER summarize the skill's process or workflow
description: For async testing
description: I can help you with async tests when they're flaky
description: Use when tests use setTimeout/sleep and are flaky
description: Use when tests have race conditions, timing dependencies, or pass/fail inconsistently, and need stable waiting and assertion patterns
description: Use when using React Router and handling authentication redirects, and need a repeatable guard and redirect pattern
2. Keyword Coverage
Use words Claude would search for:
- Error messages: "Hook timed out", "ENOTEMPTY", "race condition"
- Symptoms: "flaky", "hanging", "zombie", "pollution"
- Synonyms: "timeout/hang/freeze", "cleanup/teardown/afterEach"
- Tools: Actual commands, library names, file types
3. Descriptive Naming
Use active voice, verb-first:
- ✅
creating-skills not skill-creation
- ✅
condition-based-waiting not async-test-helpers
4. Token Efficiency (Critical)
Problem: getting-started and frequently-referenced skills load into EVERY conversation. Every token counts.
Target word counts:
- getting-started workflows: <150 words each
- Frequently-loaded skills: <200 words total
- Other skills: <500 words (still be concise)
Techniques:
Move details to tool help:
search-conversations supports --text, --both, --after DATE, --before DATE, --limit N
search-conversations supports multiple modes and filters. Run --help for details.
Use cross-references:
# ❌ BAD: Repeat workflow details
When searching, dispatch subagent with template...
[20 lines of repeated instructions]
# ✅ GOOD: Reference other skill
Always use subagents (50-100x context savings). REQUIRED: Use [other-skill-name] for workflow.
Compress examples:
# ❌ BAD: Verbose example (42 words)
your human partner: "How did we handle authentication errors in React Router before?"
You: I'll search past conversations for React Router authentication patterns.
[Dispatch subagent with search query: "React Router authentication error handling 401"]
# ✅ GOOD: Minimal example (20 words)
Partner: "How did we handle auth errors in React Router?"
You: Searching...
[Dispatch subagent → synthesis]
Eliminate redundancy:
- Don't repeat what's in cross-referenced skills
- Don't explain what's obvious from command
- Don't include multiple examples of same pattern
Verification:
wc -w .agents/skills/skill-name/SKILL.md
Name by what you DO or core insight:
- ✅
condition-based-waiting > async-test-helpers
- ✅
using-skills not skill-usage
- ✅
flatten-with-flags > data-structure-refactoring
- ✅
root-cause-tracing > debugging-techniques
Gerunds (-ing) work well for processes:
creating-skills, testing-skills, debugging-with-logs- Active, describes the action you're taking
4. Cross-Referencing Other Skills
When writing documentation that references other skills:
Use skill name only, with explicit requirement markers:
- ✅ Good:
**REQUIRED SUB-SKILL:** Use condition-based-waiting
- ✅ Good:
**REQUIRED BACKGROUND:** You MUST understand root-cause-tracing
- ❌ Bad:
See .agents/skills/testing/test-driven-development (unclear if required)
- ❌ Bad:
@.agents/skills/testing/test-driven-development/SKILL.md (force-loads, burns context)
Why no @ links: @ syntax force-loads files immediately, consuming 200k+ context before you need them.
Flowchart Usage
digraph when_flowchart {
"Need to show information?" [shape=diamond];
"Decision where I might go wrong?" [shape=diamond];
"Use markdown" [shape=box];
"Small inline flowchart" [shape=box];
"Need to show information?" -> "Decision where I might go wrong?" [label="yes"];
"Decision where I might go wrong?" -> "Small inline flowchart" [label="yes"];
"Decision where I might go wrong?" -> "Use markdown" [label="no"];
}
Use flowcharts ONLY for:
- Non-obvious decision points
- Process loops where you might stop too early
- "When to use A vs B" decisions
Never use flowcharts for:
- Reference material → Tables, lists
- Code examples → Markdown blocks
- Linear instructions → Numbered lists
- Labels without semantic meaning (step1, helper2)
See graphviz-conventions.dot for graphviz style rules.
Visualizing for your human partner: Use render-graphs.js in this directory to render a skill's flowcharts to SVG:
./render-graphs.js ../some-skill
./render-graphs.js ../some-skill --combine
Code Examples
One excellent example beats many mediocre ones
Choose most relevant language:
- Testing techniques → TypeScript/JavaScript
- System debugging → Shell/Python
- Data processing → Python
Good example:
- Complete and runnable
- Well-commented explaining WHY
- From real scenario
- Shows pattern clearly
- Ready to adapt (not generic template)
Don't:
- Implement in 5+ languages
- Create fill-in-the-blank templates
- Write contrived examples
You're good at porting - one great example is enough.
File Organization
Self-Contained Skill
defense-in-depth/
SKILL.md # Everything inline
When: All content fits, no heavy reference needed
Skill with Reusable Tool
condition-based-waiting/
SKILL.md # Overview + patterns
ExampleHelper.kt # Working helpers to adapt
When: Tool is reusable code, not just narrative
Skill with Heavy Reference
pptx/
SKILL.md # Overview + workflows
pptxgenjs.md # 600 lines API reference
ooxml.md # 500 lines XML structure
scripts/ # Executable tools
When: Reference material too large for inline
The Iron Law (Same as TDD)
NO SKILL WITHOUT A FAILING TEST FIRST
This applies to NEW skills AND EDITS to existing skills.
Write skill before testing? Delete it. Start over.
Edit skill without testing? Same violation.
No exceptions:
- Not for "simple additions"
- Not for "just adding a section"
- Not for "documentation updates"
- Don't keep untested changes as "reference"
- Don't "adapt" while running tests
- Delete means delete
Background note: The same TDD discipline applies to documentation. Explain the principle in the skill itself instead of assuming an external prerequisite skill.
Testing All Skill Types
Different skill types need different test approaches:
Discipline-Enforcing Skills (rules/requirements)
Examples: TDD, verification-before-completion, designing-before-coding
Test with:
- Academic questions: Do they understand the rules?
- Pressure scenarios: Do they comply under stress?
- Multiple pressures combined: time + sunk cost + exhaustion
- Identify rationalizations and add explicit counters
Success criteria: Agent follows rule under maximum pressure
Technique Skills (how-to guides)
Examples: condition-based-waiting, root-cause-tracing, defensive-programming
Test with:
- Application scenarios: Can they apply the technique correctly?
- Variation scenarios: Do they handle edge cases?
- Missing information tests: Do instructions have gaps?
Success criteria: Agent successfully applies technique to new scenario
Pattern Skills (mental models)
Examples: reducing-complexity, information-hiding concepts
Test with:
- Recognition scenarios: Do they recognize when pattern applies?
- Application scenarios: Can they use the mental model?
- Counter-examples: Do they know when NOT to apply?
Success criteria: Agent correctly identifies when/how to apply pattern
Reference Skills (documentation/APIs)
Examples: API documentation, command references, library guides
Test with:
- Retrieval scenarios: Can they find the right information?
- Application scenarios: Can they use what they found correctly?
- Gap testing: Are common use cases covered?
Success criteria: Agent finds and correctly applies reference information
Common Rationalizations for Skipping Testing
| Excuse | Reality |
|---|
| "Skill is obviously clear" | Clear to you ≠ clear to other agents. Test it. |
| "It's just a reference" | References can have gaps, unclear sections. Test retrieval. |
| "Testing is overkill" | Untested skills have issues. Always. 15 min testing saves hours. |
| "I'll test if problems emerge" | Problems = agents can't use skill. Test BEFORE deploying. |
| "Too tedious to test" | Testing is less tedious than debugging bad skill in production. |
| "I'm confident it's good" | Overconfidence guarantees issues. Test anyway. |
| "Academic review is enough" | Reading ≠ using. Test application scenarios. |
| "No time to test" | Deploying untested skill wastes more time fixing it later. |
All of these mean: Test before deploying. No exceptions.
Bulletproofing Skills Against Rationalization
Skills that enforce discipline (like TDD) need to resist rationalization. Agents are smart and will find loopholes when under pressure.
Psychology note: Understanding WHY persuasion techniques work helps you apply them systematically. See persuasion-principles.md for research foundation (Cialdini, 2021; Meincke et al., 2025) on authority, commitment, scarcity, social proof, and unity principles.
Close Every Loophole Explicitly
Don't just state the rule - forbid specific workarounds:
```markdown
Write code before test? Delete it.
```
```markdown
Write code before test? Delete it. Start over.
No exceptions:
- Don't keep it as "reference"
- Don't "adapt" it while writing tests
- Don't look at it
- Delete means delete
</Good>
### Address "Spirit vs Letter" Arguments
Add foundational principle early:
```markdown
**Violating the letter of the rules is violating the spirit of the rules.**
This cuts off entire class of "I'm following the spirit" rationalizations.
Build Rationalization Table
Capture rationalizations from baseline testing (see Testing section below). Every excuse agents make goes in the table:
| Excuse | Reality |
|--------|---------|
| "Too simple to test" | Simple code breaks. Test takes 30 seconds. |
| "I'll test after" | Tests passing immediately prove nothing. |
| "Tests after achieve same goals" | Tests-after = "what does this do?" Tests-first = "what should this do?" |
Create Red Flags List
Make it easy for agents to self-check when rationalizing:
## Red Flags - STOP and Start Over
- Code before test
- "I already manually tested it"
- "Tests after achieve the same purpose"
- "It's about spirit not ritual"
- "This is different because..."
**All of these mean: Delete code. Start over with TDD.**
Update CSO for Violation Symptoms
Add to description: symptoms of when you're ABOUT to violate the rule:
description: use when implementing any feature or bugfix, before writing implementation code
RED-GREEN-REFACTOR for Skills
Follow the TDD cycle:
RED: Write Failing Test (Baseline)
Run pressure scenario with subagent WITHOUT the skill. Document exact behavior:
- What choices did they make?
- What rationalizations did they use (verbatim)?
- Which pressures triggered violations?
This is "watch the test fail" - you must see what agents naturally do before writing the skill.
GREEN: Write Minimal Skill
Write skill that addresses those specific rationalizations. Don't add extra content for hypothetical cases.
Run same scenarios WITH skill. Agent should now comply.
REFACTOR: Close Loopholes
Agent found new rationalization? Add explicit counter. Re-test until bulletproof.
Testing methodology: See testing-skills-with-subagents.md for the complete testing methodology:
- How to write pressure scenarios
- Pressure types (time, sunk cost, authority, exhaustion)
- Plugging holes systematically
- Meta-testing techniques
Anti-Patterns
❌ Narrative Example
"In session 2025-10-03, we found empty projectDir caused..."
Why bad: Too specific, not reusable
❌ Multi-Language Dilution
example-js.js, example-py.py, example-go.go
Why bad: Mediocre quality, maintenance burden
❌ Code in Flowcharts
step1 [label="import fs"];
step2 [label="read file"];
Why bad: Can't copy-paste, hard to read
❌ Generic Labels
helper1, helper2, step3, pattern4
Why bad: Labels should have semantic meaning
STOP: Before Moving to Next Skill
After writing ANY skill, you MUST STOP and complete the deployment process.
Do NOT:
- Create multiple skills in batch without testing each
- Move to next skill before current one is verified
- Skip testing because "batching is more efficient"
The deployment checklist below is MANDATORY for EACH skill.
Deploying untested skills = deploying untested code. It's a violation of quality standards.
Skill Creation Checklist (TDD Adapted)
IMPORTANT: Track EACH checklist item in the task/state system available in the current environment. In this repository, reflect progress in the active task state file under .agents/state/tasks/ and keep .agents/state/INDEX.md aligned instead of assuming a specific todo tool exists.
RED Phase - Write Failing Test:
GREEN Phase - Write Minimal Skill:
REFACTOR Phase - Close Loopholes:
Quality Checks:
Deployment:
Discovery Workflow
How future Claude finds your skill:
- Encounters problem ("tests are flaky")
- Finds SKILL (description matches)
- Scans overview (is this relevant?)
- Reads patterns (quick reference table)
- Loads example (only when implementing)
Optimize for this flow - put searchable terms early and often.
The Bottom Line
Creating skills IS TDD for process documentation.
Same Iron Law: No skill without failing test first.
Same cycle: RED (baseline) → GREEN (write skill) → REFACTOR (close loopholes).
Same benefits: Better quality, fewer surprises, bulletproof results.
If you follow TDD for code, follow it for skills. It's the same discipline applied to documentation.
