Writing Skills

Overview

Writing skills IS Test-Driven Development applied to process documentation.

Skills are written to ${SUPERPOWERS_SKILLS_ROOT} (cloned to ~/.config/superpowers/skills/). You edit skills in your local branch of this repository.

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.

See skills/testing/test-driven-development for the fundamental RED-GREEN-REFACTOR cycle. This skill adapts TDD to documentation.

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 conventions (put in CLAUDE.md)

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

All skills are in the skills repository at ${SUPERPOWERS_SKILLS_ROOT}:

${SUPERPOWERS_SKILLS_ROOT}
  skill-name/
    SKILL.md              # Main reference (required)
    supporting-file.*     # Only if needed

Flat namespace - all skills in one searchable location

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

---
name: Human-Readable Name
description: One-line summary of what this does
when_to_use: when [trigger/situation]
version: 5.1.0
languages: all | [typescript, python] | etc
dependencies: (optional) Required tools/libraries
---

# 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 when_to_use

Purpose: Claude reads when_to_use to decide which skills to load for a given task. Make it answer: "Should I read this skill right now?"

Format: Start with "when" to complete "Use [skill-path] when [your text]"

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

# ❌ BAD: Too abstract, doesn't start with "when"
when_to_use: For async testing

# ❌ BAD: Mentions technology but skill isn't specific to it
when_to_use: when tests use setTimeout/sleep and are flaky

# ✅ GOOD: Starts with "when", describes problem not language symptom
when_to_use: when tests have race conditions, timing dependencies, or pass/fail inconsistently

# ✅ GOOD: Technology-specific skill with explicit trigger
when_to_use: when using React Router and handling authentication redirects

Example find-skills output:

Use skills/testing/condition-based-waiting/SKILL.md when tests have race conditions, timing dependencies, or pass/fail inconsistently

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
✅ testing-skills-with-subagents not subagent-skill-testing

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:

# ❌ BAD: Document all flags in SKILL.md
search-conversations supports --text, --both, --after DATE, --before DATE, --limit N

# ✅ GOOD: Reference --help
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). See skills/using-skills 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
# getting-started workflows: aim for <150 each
# Other frequently-loaded: aim for <200 total

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. Content Repetition

Mention key concepts multiple times:

In description
In when_to_use
In overview
In section headers

Grep hits from multiple places = easier discovery

5. Cross-Referencing Other Skills

When writing documentation that references other skills:

Use path format without @ prefix or /SKILL.md suffix:

✅ Good: skills/testing/test-driven-development
✅ Good: skills/debugging/systematic-debugging
❌ Bad: @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.

To read a skill reference: Use Read tool on ${SUPERPOWERS_SKILLS_ROOT}/category/skill-name/SKILL.md

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.

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

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

See skills/testing/test-driven-development for why this matters. Same principles apply to documentation.

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 when_to_use: symptoms of when you're ABOUT to violate the rule:

when_to_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.

See skills/testing-skills-with-subagents for:

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: Use TodoWrite to create todos for EACH checklist item below.

RED Phase - Write Failing Test:

Create pressure scenarios (3+ combined pressures for discipline skills)
Run scenarios WITHOUT skill - document baseline behavior verbatim
Identify patterns in rationalizations/failures

GREEN Phase - Write Minimal Skill:

Name describes what you DO or core insight
YAML frontmatter with rich when_to_use (include symptoms!)
Keywords throughout for search (errors, symptoms, tools)
Clear overview with core principle
Address specific baseline failures identified in RED
Code inline OR @link to separate file
One excellent example (not multi-language)
Run scenarios WITH skill - verify agents now comply

REFACTOR Phase - Close Loopholes:

Identify NEW rationalizations from testing
Add explicit counters (if discipline skill)
Build rationalization table from all test iterations
Create red flags list
Re-test until bulletproof

Quality Checks:

Small flowchart only if decision non-obvious
Quick reference table
Common mistakes section
No narrative storytelling
Supporting files only for tools or heavy reference

Deployment:

Commit skill to git and push to your fork (if configured)
Consider contributing back via PR (if broadly useful)

Discovery Workflow

How future Claude finds your skill:

Encounters problem ("tests are flaky")
Searches skills using find-skills tool (searches skills repository)
Finds SKILL.md (rich when_to_use 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.