| name | writing-skill |
| description | Use when creating new skills, editing existing skills, or verifying skills work before deployment |
Writing Skills
Overview
Writing skills IS Test-Driven Development applied to process documentation.
Personal skills live in agent-specific directory (~/.config/ai/skills)
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.
What is a Skill?
A skill is a reference guide for proven techniques, patterns, or tools. Skills help future agent 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
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 conventions (put in 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
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):
- Only two fields supported:
name and description
- Max 1024 characters total
name: Use letters, numbers, and hyphens only (no parentheses, special chars)description: Third-person, describes ONLY when to use (NOT what it does)
- Start with "Use when..." to focus on triggering conditions
- Include specific symptoms, situations, and contexts
- NEVER summarize the skill's process or workflow (see CSO section for why)
- Keep under 500 characters if possible
---
name: Skill-Name-With-Hyphens
description: Use when [specific triggering conditions and symptoms]
---
# 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
agent Search Optimization (CSO)
Critical for discovery: Future agent needs to FIND your skill
1. Rich Description Field
Purpose: agent 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: Description = When to Use, NOT What the Skill Does
The description should ONLY describe triggering conditions. Do NOT summarize the skill's process or workflow in the description.
Why this matters: Testing revealed that when a description summarizes the skill's workflow, agent may follow the description instead of reading the full skill content. A description saying "code review between tasks" caused agent 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 just "Use when executing implementation plans with independent tasks" (no workflow summary), agent correctly read the flowchart and followed the two-stage review process.
The trap: Descriptions that summarize workflow create a shortcut agent will take. The skill body becomes documentation agent 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 in the current session
description: Use when implementing any feature or bugfix, 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
description: Use when using React Router and handling authentication redirects
2. Keyword Coverage
Use words agent 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 skills/path/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 clear-writing
- ✅ Good:
**REQUIRED BACKGROUND:** You MUST understand clear-writing
- ❌ Bad:
See skills/clear-writing (unclear if required)
- ❌ Bad:
@skills/clear-writing/SKILL.md (force-loads, burns context)
Why no @ links: @ syntax force-loads files immediately, consuming 200k+ context before you need them.
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
example.ts # 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
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
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
Discovery Workflow
How future agent 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.
