Skill Authoring Guide

Overview

Writing effective Claude Code skills requires Test-Driven Development (TDD) and persuasion principles from compliance research. We treat skill writing as process documentation that needs empirical validation rather than just theoretical instruction. Skills are behavioral interventions designed to change model behavior in measurable ways.

By using TDD, we ensure skills address actual failure modes identified through testing. Optimized descriptions improve discovery, while a modular structure supports progressive disclosure to manage token usage. This framework also includes anti-rationalization patterns to prevent the assistant from bypassing requirements.

The Iron Law

NO SKILL WITHOUT A FAILING TEST FIRST

Every skill must begin with documented evidence of Claude failing without it. This validates that you are solving a real problem. No implementation should proceed without a failing test, and no completion claim should be accepted without evidence. Detailed enforcement patterns for adversarial verification and coverage gates are available in imbue:proof-of-work.

Skill Types

We categorize skills into three types: Technique skills for specific methods, Pattern skills for recurring solutions, and Reference skills for quick lookups and checklists. This helps organize interventions into the most effective format for the task.

Quick Start

Skill Analysis

```bash

Analyze skill complexity

python scripts/analyze.py

Estimate tokens

python scripts/tokens.py ```

Validation

```bash

Validate skill structure

python scripts/abstract_validator.py --check ```

Verification: Run analysis and review token estimates before proceeding.

Description Optimization

Skill descriptions must be optimized for semantic search and explicit triggering. Follow the formula [What it does] + [When to use it] + [Key triggers]. Use a third-person voice (e.g., "Guides...", "Provides...") and include specific, concrete use cases. Avoid marketing language or vague phrases like "helps with coding."

Skill Character Budget (Claude Code 2.1.32+)

Skill description character budgets now scale with context window at 2% of available context. This means:

Context Window	Description Budget
200K (standard)	~4,000 characters
1M (Opus 4.6 beta)	~20,000 characters

Previously constrained skills can use more descriptive text on larger windows. However, keep descriptions concise regardless — longer is not better. The scaling primarily prevents truncation for skills with legitimately complex trigger conditions, not as an invitation to add verbose content.

Plugin Name Auto-Display (Claude Code 2.1.33+)

Plugin names are now automatically shown alongside skill descriptions in the /skills menu. Do not repeat the plugin name in skill descriptions — it is redundant and wastes character budget. Focus descriptions on what the skill does and when to use it.

The TDD Cycle for Skills

RED Phase: Document Baseline Failures

Establish empirical evidence that an intervention is needed. Create at least three pressure scenarios that combine time pressure and ambiguity. Run these in a fresh instance without the skill active and document the exact failures, such as skipped error handling or missing validation.

GREEN Phase: Minimal Skill Implementation

Create the smallest intervention that addresses the documented failures. Write the SKILL.md with required frontmatter and content that directly counters the baseline failures. Include one example of correct behavior and verify that the same pressure scenarios now show measurable improvement.

REFACTOR Phase: Anti-Rationalization

Eliminate the ability for Claude to explain away requirements. Run pressure scenarios with the skill active to identify common rationalizations, such as claiming a task is "too simple" for the full process. Add explicit counters, such as exception tables and red flag lists, until rationalizations stop.

Anti-Rationalization

Skills must explicitly counter patterns where Claude attempts to bypass requirements. Common excuses include claiming a task is "too simple" or that a "spirit vs letter of the law" approach is sufficient. Skills should include red flag lists for self-checking, such as "Stop if you think: this is too simple for the full process." When exceptions are necessary, document them explicitly to prevent unauthorized shortcuts.

Module References

For detailed implementation guidance:

• TDD Methodology: See modules/tdd-methodology.md for RED-GREEN-REFACTOR cycle details
• Persuasion Principles: See modules/persuasion-principles.md for compliance research and techniques
• Description Writing: See modules/description-writing.md for discovery optimization
• Progressive Disclosure: See modules/progressive-disclosure.md for file structure patterns
• Anti-Rationalization: See modules/anti-rationalization.md for bulletproofing techniques
• Graphviz Conventions: See modules/graphviz-conventions.md for process diagram standards
• Testing with Subagents: See abstract:subagent-testing skill for pressure testing methodology
• Deployment Checklist: See modules/deployment-checklist.md for final validation

Deployment and Quality Gates

Before deploying, verify that the RED, GREEN, and REFACTOR phases are complete and documented. Frontmatter must be valid, descriptions optimized, and line counts kept under 500 lines. Ensure all module references are valid and at least one concrete example is included.

Scribe Validation

All markdown files must pass scribe validation. This includes a slop scan to ensure a score under 2.5 and doc verification to confirm all file paths and command examples work. Bullet-to-prose ratios must remain under 60% to maintain readability. Use Skill(scribe:slop-detector) and Skill(scribe:doc-verify) for these checks.

Integration and Best Practices

Individual skills are created using skill-authoring, while modular-skills handles the architecture of larger structures. skills-eval provides ongoing quality assessment. Avoid the common pitfall of writing skills based on theoretical behavior; always use documented failures to guide development. Use progressive disclosure to prevent monolithic files and ensure that each intervention remains focused and token-efficient.

Troubleshooting

Common Issues

Skill not loading Check YAML frontmatter syntax and required fields

Token limits exceeded Use progressive disclosure - move details to modules

Modules not found Verify module paths in SKILL.md are correct