architecture-evolution
Manage architecture changes with impact analysis, ADR generation, and migration planning. Use when relevant to the task.
Browse published AI skills maintained by jmagly. Compare skill descriptions and follow each source repository for setup instructions.
Indexed skills
72Repository stars across indexed skills
5,722Repository forks
654Average repository stars per indexed skill
79Repository stars may repeat across skills from the same repository.
Manage architecture changes with impact analysis, ADR generation, and migration planning. Use when relevant to the task.
Generate executive-ready performance summaries with insights and recommendations. Use when relevant to the task.
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.
Execute Python tests with pytest, supporting fixtures, markers, coverage, and parallel execution. Use for Python test automation.
Assesses workspace alignment and suggests cleanup or realignment actions at key transition points. Use when relevant to the task.
Combine multiple voice profiles with weighted mixing to create hybrid voices. Use when relevant to the task.
Analyze GitHub repositories for structure, documentation, dependencies, and contribution patterns. Use for codebase understanding and health assessment.
Rapid incident classification, severity assessment, and response coordination. Use when relevant to the task.
Gather and analyze competitive intelligence from multiple sources. Use when relevant to the task.
Merge multiple documentation sources (docs, GitHub, PDF) with conflict detection. Use when combining docs + code for complete skill coverage.
Detect requests for iterative AI task loops and invoke the Ralph command
Verify bidirectional traceability from requirements to code to tests. Use when relevant to the task.
Detects AI-generated writing patterns and suggests authentic alternatives. Auto-applies when reviewing content, editing documents, generating text, or when user mentions writing quality, AI detection, authentic...
Detect orphaned tests, obsolete assertions, and test-code misalignment. Use for test suite maintenance, cleanup, and traceability validation.
Package skills into uploadable ZIP files for Claude. Use after skill-builder/skill-enhancer to create final upload package. Use when relevant to the task.
Validate AIWG configuration files and project setup for correctness and completeness. Use when relevant to the task.
Multi-stage quality assurance protocol for marketing assets with channel-specific validation. Use when relevant to the task.
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.
Analyze test coverage, identify gaps, and recommend test improvements. Use when relevant to the task.
Route natural language requests to appropriate skills and workflows. Use when relevant to the task.
Auto-generate test data factories from schemas, types, or models. Use when creating test data infrastructure, setting up fixtures, or reducing test setup boilerplate.
Split large documentation (10K+ pages) into focused sub-skills with intelligent routing. Use for massive doc sites like Godot, AWS, or MSDN.
Detect orphaned tests, obsolete assertions, and test-code misalignment. Use for test suite maintenance, cleanup, and traceability validation. Use when relevant to the task.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.