writing-skills
Use when creating new skills, editing existing skills, or verifying skills work before deployment
What this skill does
# Writing Skills
## Overview
**Writing skills IS Test-Driven Development applied to process documentation.**
**Personal skills live in agent-specific directories (`~/.claude/skills` for Claude Code, `~/.codex/skills` for Codex)**
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.
**REQUIRED BACKGROUND:** You MUST understand superpowers:test-driven-development before using this skill. That skill defines the fundamental RED-GREEN-REFACTOR cycle. This skill adapts TDD to documentation.
**Official guidance:** For Anthropic's official skill authoring best practices, see anthropic-best-practices.md.
## 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)
- Mechanical constraints (if enforceable with regex/validation, automate it)
## 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)
references/ # Cold reference material
supporting-file.* # Only if needed
```
**Flat namespace** - all skills in one searchable namespace
**Separate files for:** Heavy reference (100+ lines), reusable tools/scripts
**Keep inline:** Principles, concepts, code patterns (< 50 lines)
## 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
- **NEVER summarize the skill's process or workflow** (see CSO section)
- Keep under 500 characters if possible
```markdown
---
name: Skill-Name-With-Hyphens
description: Use when [specific triggering conditions and symptoms]
---
# Skill Name
## Overview
Core principle in 1-2 sentences.
## When to Use
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.
## Common Mistakes
What goes wrong + fixes
```
## Claude Search Optimization (CSO)
**Critical for discovery:** Future Claude needs to FIND your skill.
### Description Field
**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.
**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 showed TWO reviews.
**The trap:** Descriptions that summarize workflow create a shortcut Claude will take. The skill body becomes documentation Claude skips.
```yaml
# BAD: Summarizes workflow - Claude may follow this instead of reading skill
description: Use when executing plans - dispatches subagent per task with code review between tasks
# GOOD: Just triggering conditions, no workflow summary
description: Use when executing implementation plans with independent tasks in the current session
```
### 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
### Descriptive Naming
**Use active voice, verb-first:**
- `creating-skills` not `skill-creation`
- `condition-based-waiting` not `async-test-helpers`
**Gerunds (-ing) work well for processes:** `creating-skills`, `testing-skills`, `debugging-with-logs`
### Cross-Referencing Other Skills
Use skill name only, with explicit requirement markers:
- Good: `**REQUIRED SUB-SKILL:** Use superpowers:test-driven-development`
- Good: `**REQUIRED BACKGROUND:** You MUST understand superpowers:systematic-debugging`
- Bad: `See skills/testing/test-driven-development` (unclear if required)
- 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.
## 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
**REQUIRED BACKGROUND:** The superpowers:test-driven-development skill explains why this matters. Same principles apply to documentation.
## Anti-Patterns
- **Narrative example:** "In session 2025-10-03, we found..." -- Too specific, not reusable
- **Multi-language dilution:** example-js.js, example-py.py, example-go.go -- Mediocre quality, maintenance burden
- **Code in flowcharts:** `step1 [label="import fs"]` -- Can't copy-paste, hard to read
- **Generic labels:** helper1, helper2, step3 -- Labels should have semantic meaning
## 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.
## Reference Material
| Document | Contents |
| -------- | -------- |
| [references/testing-skills.md](references/testing-skills.md) | Testing by skill type, common rationalizations, bulletproofing, RED-GREEN-REFACTOR Related in Writing & Docs
jax-development
IncludedUse this skill when the user is writing, debugging, profiling, refactoring, reviewing, benchmarking, parallelising, exporting, or explaining JAX code, or when they mention JAX, jax.numpy, jit, grad, value_and_grad, vmap, scan, lax, random keys, pytrees, jax.Array, sharding, Mesh, PartitionSpec, NamedSharding, pmap, shard_map, Pallas, XLA, StableHLO, checkify, profiler, or the JAX repo. It helps turn NumPy or PyTorch-style code into pure functional JAX, fix tracer/control-flow/shape/PRNG bugs, remove recompiles and host-device syncs, choose transforms and sharding strategies, inspect jaxpr/lowering/IR, and benchmark compiled code correctly.
nature-article-writer
IncludedDrafts, rewrites, diagnostically critiques, and style-calibrates primary research manuscripts for Nature and Nature Portfolio journals. Use when the user wants a Nature-style title, summary paragraph or abstract, introduction, results, discussion, methods, figure legends, presubmission enquiry, cover letter, reviewer response, or when a scientific draft sounds generic, jargon-heavy, structurally weak, or AI-ish and needs precise, broad-reader-friendly prose without inventing data, analyses, or references. Best for primary research articles and letters rather than reviews or press releases unless explicitly adapting one.
deckrd
IncludedDocument-driven framework that derives requirements, specifications, implementation plans, and executable tasks from goals through structured AI dialogue. Use when user says "write requirements", "create spec", "plan implementation", "derive tasks", "structure this feature", "break down into tasks", or "document this module". Also use for reverse engineering existing code into docs (/deckrd rev). Do NOT use for direct code writing — use /deckrd-coder after tasks are generated. Do NOT use when the user only wants to run or fix existing code without planning.
clinical-decision-support
IncludedGenerate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.
handling-sf-data
IncludedSalesforce data operations with 130-point scoring. Use this skill to create, update, delete, bulk import/export, generate test data, and clean up org records using sf CLI and anonymous Apex. TRIGGER when: user creates test data, performs bulk import/export, uses sf data CLI commands, needs data factory patterns for Apex tests, or needs to seed/clean records in a Salesforce org. DO NOT TRIGGER when: SOQL query writing only (use querying-soql), Apex test execution (use running-apex-tests), or metadata deployment (use deploying-metadata).
accelint-ac-to-playwright
IncludedConvert and validate acceptance criteria for Playwright test automation. Use when user asks to (1) review/evaluate/check if AC are ready for automation, (2) assess if AC can be converted as-is, (3) validate AC quality for Playwright, (4) turn AC into tests, (5) generate tests from acceptance criteria, (6) convert .md bullets or .feature Gherkin files to Playwright specs, (7) create test automation from requirements. Handles both bullet-style markdown and Gherkin syntax with JSON test plan generation and validation.