llms-txt-support
Detect and use llms.txt files for LLM-optimized documentation. Use when checking if a site has LLM-ready docs before scraping.
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.
Detect and use llms.txt files for LLM-optimized documentation. Use when checking if a site has LLM-ready docs before scraping.
Multi-stakeholder approval routing with status tracking and escalation. Use when relevant to the task.
Package skills into uploadable ZIP files for Claude. Use after skill-builder/skill-enhancer to create final upload package.
Synthesize audience insights from multiple data sources into unified personas and segments. Use when relevant to the task.
Suggest and apply fixes for flaky tests based on detected patterns. Use after flaky-detect identifies unreliable tests that need repair.
Extract text, tables, and images from PDF files. Use when converting PDF documentation, manuals, or reports to searchable text.
Orchestrate marketing data collection, transformation, and reporting workflows. Use when relevant to the task.
Scrape documentation websites into organized reference files. Use when converting docs sites to searchable references or building Claude skills.
Identify flaky tests from CI history and test execution patterns. Use when debugging intermittent test failures, auditing test reliability, or improving CI stability.
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...
Execute JavaScript/TypeScript tests with Vitest, supporting coverage, watch mode, and parallel execution. Use for JS/TS test automation.
Unified brand compliance validation across visual, verbal, and legal dimensions. Use when relevant to the task.
Scrape documentation websites into organized reference files. Use when converting docs sites to searchable references or building Claude skills.
Load, validate, and populate templates consistently across frameworks. Use when relevant to the task.
Build Claude skills from extracted documentation. Use after doc-scraper/pdf-extractor to generate uploadable skill packages. Use when relevant to the task.
Build Claude skills from extracted documentation. Use after doc-scraper/pdf-extractor to generate uploadable skill packages.
Aggregate multi-reviewer feedback into consolidated, actionable recommendations. Use when relevant to the task.
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. Use when relevant to the task.
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.
Validate skill quality, completeness, and adherence to standards. Use before packaging to ensure skill meets quality requirements. Use when relevant to the task.
Create, manage, and validate Python virtual environments. Use for project isolation and dependency management.
Detect and use llms.txt files for LLM-optimized documentation. Use when checking if a site has LLM-ready docs before scraping.
AI-powered enhancement of skill SKILL.md files. Use to transform basic templates into comprehensive, high-quality skill documentation. 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.