claude-night-market

Triggers: refine, code quality, clean code, refactor, duplication, algorithm efficiency, complexity reduction, code smell, anti-slop, craft Analyze and improve living code quality: duplication, algorithmic efficiency, clean code principles, architectural fit, anti-slop patterns, and error handling robustness. Use when: improving code quality, reducing AI slop, refactoring for clarity, optimizing algorithms, applying clean code principles DO NOT use when: removing dead/unused code (use conserve:bloat-detector). DO NOT use when: reviewing for bugs (use pensive:bug-review). DO NOT use when: selecting architecture paradigms (use archetypes skills). This skill actively improves living code, complementing bloat detection (dead code removal) with quality refinement (living code improvement).

Triggers: safety, critical, NASA, power of 10, defensive coding, assertions, bounds checking Guidelines from NASA's Power of 10 rules for writing robust, verifiable code. Adapted for general software development with context-appropriate rigor. Use when: Writing critical code paths, reviewing for robustness, improving code quality DO NOT use: As rigid requirements for all code - match rigor to consequence

Audit shell scripts for correctness, portability, and common pitfalls. Triggers: shell script, bash, sh, script review, pipeline, exit code Use when: reviewing shell scripts, CI scripts, hook scripts, wrapper scripts DO NOT use when: creating new scripts - use attune:workflow-setup

Detect codebase bloat through progressive analysis: dead code, duplication, complexity, documentation bloat. Triggers: bloat detection, dead code, code cleanup, duplication, technical debt, unused code Use when: context usage high, quarterly maintenance, pre-release cleanup, before refactoring DO NOT use when: active feature development, time-sensitive bugs, codebase < 1000 lines

Automatic context management with graceful handoff to continuation subagent. Triggers: context pressure, 80% threshold, auto-clear, context full, continuation, session state, checkpoint Use when: Context usage approaches 80% during long-running tasks. This skill enables automatic continuation without manual /clear. The key insight: Subagents have fresh context windows. By delegating remaining work to a continuation subagent, we achieve effective "auto-clear" without stopping the workflow.

Triggers: KISS, YAGNI, SOLID, clean code, code quality, refactor, design principles Provides guidance on fundamental software design principles to reduce complexity, prevent over-engineering, and improve maintainability.

Systematic methodology to reduce skill file size through externalization, consolidation, and progressive loading patterns. Triggers: large skill, skill optimization, skill size, 300 lines, inline code, skill refactoring, skill context reduction, skill modularization Use when: skills exceed 300 lines, multiple code blocks (10+) with similar functionality, heavy Python inline with markdown, functions >20 lines embedded DO NOT use when: skill is under 300 lines and well-organized. DO NOT use when: creating new skills - use modular-skills instead. Consult this skill when skills-eval shows "Large skill file" warnings.

Triggers: verbose, bloat, concise, compress, direct, efficient response Eliminates response bloat including emojis, filler words, hedging language, hype, and unnecessary framing. Includes termination and directness guidelines.

Triggers: source, cite, reference, factual claim, verify, attribution Intelligent sourcing that requires citations only for high-value factual claims, balancing accuracy with token efficiency.

Generate language-specific Makefile with common development targets

Configure comprehensive three-layer pre-commit quality system with linting, type checking, and testing enforcement

Socratic questioning and ideation methodology for project conception using structured brainstorming frameworks

Systematic task execution with checkpoint validation, progress tracking, and quality gates

Transform project brief into detailed, testable specifications using spec-driven development methodology

Multi-LLM deliberation framework for strategic decisions through pressure-based expert consultation

Inline reversibility assessment for embedded War Room escalation from other commands

Configure GitHub Actions workflows for CI/CD (test, lint, typecheck, publish)

Enforces "prove before claim" discipline - validation, testing, and evidence requirements before declaring work complete. Triggers: validation, definition-of-done, proof, acceptance-criteria, testing, completion, finished, done, working, should work, configured, ready to use, implemented, fixed, improvement validated, workflow optimized, performance improved, issue resolved. Use when claiming work is complete, recommending solutions, or finishing implementations. Do not use when asking questions or for work clearly in-progress. MANDATORY: This skill is required before any completion claim.

Prevents sycophantic reasoning through checklist-based analysis, categorical integrity, and evidence-following to uncomfortable conclusions. Triggers: conflict, disagreement, debate, ethical, controversial, pushback, interpersonal analysis, competing values, adjudication, "who is right", moral dilemma, harm assessment, ethical question, controversial claim. Red Flags: "I agree that", "You're right", "Great point", "Absolutely", "That's a fair point", "I can see why", agreement without validation, softening conclusions, hedging without evidence, retracting under pressure. Use when analyzing conflicts, evaluating ethical claims, or noticing sycophantic thought patterns. Do not use for routine implementation or simple factual questions. CRITICAL: This skill overrides conversational tendencies toward politeness. Agreement requires validity and accuracy.

Triggers: workflow error, inefficient execution, workflow failure, execution monitor Monitor workflow executions for errors and inefficiencies. When issues are detected, automatically create GitHub issues for workflow improvements via /fix-workflow. Use when: workflows fail, timeout, or show inefficient patterns DO NOT use when: normal workflow execution, simple command errors

Surfaces expert frameworks and proven methodologies before creating OR evaluating skills, hooks, agents, or commands. Helps select approaches from domain masters. Triggers: methodology, framework, expert approach, best practices, masters, proven method, domain expertise, how should I approach, what's the best way, evaluate skill, review methodology, is this grounded, optimization check. Use when starting creation workflows, evaluating methodology gaps, or seeking domain expertise. Do not use if you already have a specific methodology or are fixing syntax/structural issues.

Architect skills as modular blocks to control token usage and complexity. Triggers: skills, architecture, modular, design-patterns, modularity, skill design, skill architecture, modularization, token optimization, skill structure, refactoring skills, new skill creation, skill complexity. Use when creating skills >150 lines, breaking down monolithic skills, or planning new architecture. Do not use for evaluating existing skills (use skills-eval) or writing human-facing prose (use writing-clearly-and-concisely). Check this skill before starting any new skill development.

Guide to effective Claude Code skill authoring using TDD methodology and persuasion principles. Triggers: skills, validation, skill, authoring, tdd, skill authoring, skill writing, new skill, TDD skills, skill creation, skill best practices, skill validation, skill deployment, skill compliance. Use when creating new skills, improving compliance, or validating quality before deployment. Do not use for evaluating existing skills (use skills-eval) or analyzing architecture (use modular-skills). Follow the Iron Law: write a failing test before writing any skill.

Evaluate and improve Claude skill quality through auditing. Triggers: quality-assurance, skills, optimization, tool-use, performance-metrics, skill audit, quality review, compliance check, improvement suggestions, token usage analysis, skill evaluation, skill assessment, skill optimization, skill standards, skill metrics, skill performance. Use when reviewing skill quality, preparing skills for production, or auditing existing skills. Do not use when creating new skills (use modular-skills) or writing prose (use writing-clearly-and-concisely). Use this skill before shipping any skill to production.

TDD-style testing methodology for skills using fresh subagent instances to prevent priming bias and validate skill effectiveness. Triggers: test skill, validate skill, skill testing, subagent testing, fresh instance testing, TDD for skills, skill validation Use when: validating skill improvements, testing skill effectiveness, preventing priming bias, measuring skill impact on behavior DO NOT use when: implementing skills (use skill-authoring instead), creating hooks (use hook-authoring instead)

Capture and retrieve PR review knowledge in project memory palaces

Generate or remediate documentation with human-quality writing and style adherence. Triggers: documentation, generate docs, write docs, technical writing, generate documentation, write readme, create guide, doc generation, remediate docs, polish content, clean up docs. Use when creating new documentation, rewriting AI-generated content, or applying style profiles. Do not use for slop detection only (use slop-detector) or learning styles (use style-learner).

Shared utilities and constants for scribe plugin skills. This module provides common patterns, word lists, and utilities used across slop-detector, style-learner, and doc-generator.

Detect and flag AI-generated content markers in documentation and prose. Triggers: ai slop, ai-generated, llm markers, chatgpt phrases, claude tells, slop detection, ai cleanup, humanize text, remove ai markers, detect chatgpt, detect llm, writing quality, ai tells. Use when reviewing documentation for AI markers, cleaning up LLM-generated content, or auditing prose quality. Do not use when generating new content (use doc-generator) or learning writing styles (use style-learner).

Triggers: writing style, voice, tone, style guide, exemplar, style learning Learn and extract writing style patterns from exemplar text for consistent application. Triggers: learn style, extract style, style profile, writing voice, tone analysis, style guide generation, exemplar analysis Use when: creating a style guide from existing content, ensuring consistency across documents, learning a specific author's voice, customizing AI output style DO NOT use when: detecting AI slop - use slop-detector instead. DO NOT use when: just need to clean up existing content - use doc-generator with --remediate. Use this skill to build style profiles from exemplar text.

Delegate tasks to external LLM services (Gemini, Qwen) with quota, logging, and error handling.

Gemini CLI delegation workflow implementing delegation-core for Google's Gemini models.

Qwen CLI delegation workflow implementing delegation-core for Alibaba's Qwen models.