writing-skills

Automates test-driven documentation to validate Claude skills across agent-specific directories.

3|Updated Nov 19, 2025
One-click install
npx skills add https://github.com/seanGSISG/crispy-claude --skill writing-skills-seangsisg
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: writing-skills
Source: https://github.com/seanGSISG/crispy-claude/tree/main/.claude/skills/writing-skills
Command: npx skills add https://github.com/seanGSISG/crispy-claude --skill writing-skills-seangsisg

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Creating effective AI skills that agents consistently discover and follow, especially under pressure, requires a disciplined approach to documentation. This skill applies Test-Driven Development (TDD) to skill creation.

Core Features & Use Cases

  • TDD for Skills: Guides through a RED-GREEN-REFACTOR cycle: testing with subagents without the skill, writing the skill to address observed failures, and iterating to close loopholes.
  • Pressure Scenario Testing: Emphasizes creating realistic scenarios with combined pressures (time, sunk cost, authority) to test agent compliance.
  • CSO (Claude Search Optimization): Provides guidelines for rich descriptions, keyword coverage, and token efficiency to ensure skills are discoverable and load efficiently.

Quick Start

Use the writing-skills skill to create a new skill for 'advanced-git-workflows', ensuring it's bulletproof against agent rationalization.

Frequently Asked Questions about writing-skills

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I apply test-driven development to create AI skills that agents actually follow?

Test-driven development for skills uses a RED-GREEN-REFACTOR cycle: first test the skill's behavior with subagents without it to identify gaps, then write the skill to address those failures, and iterate to close loopholes. This ensures agents consistently discover and comply with the skill under real-world pressure.

What's the best way to test if my AI skill will hold up under pressure scenarios?

Create realistic pressure scenarios combining time constraints, sunk cost, and authority pressures, then use subagents to simulate actual usage. This reveals whether agents rationalize away the skill or comply consistently, exposing weaknesses before deployment.

How do I ensure my AI skill is discoverable and loads efficiently?

Claude Search Optimization (CSO) guidelines cover rich descriptions, comprehensive keyword coverage, and token efficiency. Apply these during skill documentation to ensure the skill appears in relevant searches and loads without unnecessary overhead.

What documentation structure should I use when writing an AI skill?

Use concise frontmatter paired with structured SKILL.md and explicit validation workflows. This combination delivers clarity about what the skill does, when to use it, and how to verify it works correctly across agent-specific directories.

Can I use this approach to update existing skills, or only for new ones?

The test-driven approach applies to creation, editing, and verification of skills. Apply it during red-green-refactor cycles whenever you modify a skill to ensure changes close behavioral gaps and maintain compliance.