Nm Abstract Skill Authoring
v1.8.3Guide to creating Claude Code skills using TDD methodology and persuasion principles. Use for new skill development
Like a lobster shell, security has layers — review code before you run it.
Runtime requirements
Night Market Skill — ported from claude-night-market/abstract. For the full experience with agents, hooks, and commands, install the Claude Code plugin.
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 (Sonnet/Haiku) | ~4,000 characters |
| 1M (Opus 4.6 GA) | ~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.mdfor RED-GREEN-REFACTOR cycle details - Persuasion Principles: See
modules/persuasion-principles.mdfor compliance research and techniques - Description Writing: See
modules/description-writing.mdfor discovery optimization - Progressive Disclosure: See
modules/progressive-disclosure.mdfor file structure patterns - Anti-Rationalization: See
modules/anti-rationalization.mdfor bulletproofing techniques - Graphviz Conventions: See
modules/graphviz-conventions.mdfor process diagram standards - Testing with Subagents: See
abstract:subagent-testingskill for pressure testing methodology - Deployment Checklist: See
modules/deployment-checklist.mdfor 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 Agent(scribe:doc-verifier) 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.
Skill Directory Variable (2.1.69+)
Skills can reference their own directory using
${CLAUDE_SKILL_DIR} in SKILL.md content. This
variable resolves to the absolute path of the
directory containing the SKILL.md file. Use it for
referencing sibling files, data assets, or module
paths without hardcoding absolute paths:
See `${CLAUDE_SKILL_DIR}/modules/advanced.md`
for detailed patterns.
Run: `python3 ${CLAUDE_SKILL_DIR}/scripts/check.py`
This is especially useful for skills that ship alongside scripts or data files and need portable path references that work regardless of where the plugin is installed.
Description Colon Fix (2.1.69+)
Skill descriptions containing colons (e.g.,
description: "Triggers include: X, Y, Z") previously
failed to load from SKILL.md frontmatter. This is
fixed in 2.1.69. Skills without a description: field
also now appear in the available skills list (previously
they were silently excluded).
Troubleshooting
Common Issues
Skill not loading
Check YAML frontmatter syntax and required fields.
As of 2.1.69, skills without a description: field
still appear in the skills list, but descriptions
with colons must be quoted in YAML frontmatter.
Token limits exceeded Use progressive disclosure - move details to modules
Modules not found Verify module paths in SKILL.md are correct
Comments
Loading comments...