Claude Skills by jmagly

Assesses workspace alignment and suggests cleanup or realignment actions at key transition points.

Scrape documentation websites into organized reference files. Use when converting docs sites to searchable references or building Claude skills.

Split large documentation (10K+ pages) into focused sub-skills with intelligent routing. Use for massive doc sites like Godot, AWS, or MSDN.

Detect and use llms.txt files for LLM-optimized documentation. Use when checking if a site has LLM-ready docs before scraping.

Extract text, tables, and images from PDF files. Use when converting PDF documentation, manuals, or reports to searchable text.

Merge multiple documentation sources (docs, GitHub, PDF) with conflict detection. Use when combining docs + code for complete skill coverage.

Validate skill quality, completeness, and adherence to standards. Use before packaging to ensure skill meets quality requirements.

Build Claude skills from extracted documentation. Use after doc-scraper/pdf-extractor to generate uploadable skill packages.

AI-powered enhancement of skill SKILL.md files. Use to transform basic templates into comprehensive, high-quality skill documentation.

Package skills into uploadable ZIP files for Claude. Use after skill-builder/skill-enhancer to create final upload package.

Identify flaky tests from CI history and test execution patterns. Use when debugging intermittent test failures, auditing test reliability, or improving CI stability.

Suggest and apply fixes for flaky tests based on detected patterns. Use after flaky-detect identifies unreliable tests that need repair.

Auto-generate test data factories from schemas, types, or models. Use when creating test data infrastructure, setting up fixtures, or reducing test setup boilerplate.

Run mutation testing to validate test quality beyond code coverage. Use when assessing test effectiveness, finding weak tests, or validating test suite quality.

Configure TDD enforcement via pre-commit hooks and CI coverage gates. Use when setting up test-first development workflow, adding coverage gates, or enforcing TDD practices.

Detect orphaned tests, obsolete assertions, and test-code misalignment. Use for test suite maintenance, cleanup, and traceability validation.

Reverse-engineer voice profiles from sample content by analyzing writing patterns.

Applies a voice profile to transform content. Use when user asks to write in a specific voice, match a tone, apply a style, or transform content to sound like a particular voice profile.

Combine multiple voice profiles with weighted mixing to create hybrid voices.

Generate custom voice profiles from natural language descriptions.

Multi-stakeholder approval routing with status tracking and escalation.

Synthesize audience insights from multiple data sources into unified personas and segments.

Unified brand compliance validation across visual, verbal, and legal dimensions.

Gather and analyze competitive intelligence from multiple sources.

Orchestrate marketing data collection, transformation, and reporting workflows.

Generate executive-ready performance summaries with insights and recommendations.

Multi-stage quality assurance protocol for marketing assets with channel-specific validation.

Aggregate multi-reviewer feedback into consolidated, actionable recommendations.

Review GitHub pull requests for code quality, security, and best practices. Use for automated PR feedback and approval workflows.

Analyze GitHub repositories for structure, documentation, dependencies, and contribution patterns. Use for codebase understanding and health assessment.

Run ESLint for JavaScript/TypeScript code quality and style enforcement. Use for static analysis and auto-fixing.

Execute JavaScript/TypeScript tests with Vitest, supporting coverage, watch mode, and parallel execution. Use for JS/TS test automation.

Execute Python tests with pytest, supporting fixtures, markers, coverage, and parallel execution. Use for Python test automation.

Create, manage, and validate Python virtual environments. Use for project isolation and dependency management.

Manage architecture changes with impact analysis, ADR generation, and migration planning.

Orchestrate multi-agent artifact generation with the Primary Author → Parallel Reviewers → Synthesizer → Archive pattern.

Facilitate data-driven technical decisions using embedded decision matrices and trade-off analysis.

Validate phase gate criteria with multi-agent review and generate pass/fail reports.

Rapid incident classification, severity assessment, and response coordination.

Continuous risk identification, assessment, tracking, and retirement throughout SDLC.

Generate comprehensive SDLC reports including iteration status, metrics dashboards, and executive summaries.

Execute threat modeling, vulnerability scanning, and security control validation.

Analyze test coverage, identify gaps, and recommend test improvements.

Verify bidirectional traceability from requirements to code to tests.