Agent skills
Skills you can use with AI coding agents, indexed from public GitHub repositories.
-
setup-run
Execute a `setup.aiwg.io/v1` SetupManifest, performing cross-platform installati
jmagly/aiwg 107
-
setup-validate
Validate a `setup.aiwg.io/v1` SetupManifest file against the schema and run cons
jmagly/aiwg 107
-
voice-analyze
jmagly/aiwg 107
-
voice-apply
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.
jmagly/aiwg 107
-
voice-create
jmagly/aiwg 107
-
voice-blend
jmagly/aiwg 107
-
pdf-extractor
Extract text, tables, and images from PDF files. Use when converting PDF documentation, manuals, or reports to searchable text.
jmagly/aiwg 107
-
source-unifier
Merge multiple documentation sources (docs, GitHub, PDF) with conflict detection. Use when combining docs + code for complete skill coverage.
jmagly/aiwg 107
-
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.
jmagly/aiwg 107
-
doc-splitter
Split large documentation (10K+ pages) into focused sub-skills with intelligent routing. Use for massive doc sites like Godot, AWS, or MSDN.
jmagly/aiwg 107
-
doc-scraper
Scrape documentation websites into organized reference files. Use when converting docs sites to searchable references or building Claude skills.
jmagly/aiwg 107
-
eval-loop
Configure and run the isolated eval loop pattern — generate, evaluate, refine until pass threshold met
jmagly/aiwg 107
-
pattern-selector
Recommends the right LLM pipeline pattern for a use case — simple chain, embedded agent, state machine, RAG, eval loop, or dynamic prompt
jmagly/aiwg 107
-
productionize
Production readiness review — strip prototype scaffolding, harden code, validate cost model, generate prod/ artifacts
jmagly/aiwg 107
-
prompt-engineer
Production prompt engineering — write, iterate, and refine prompts with built-in eval loop feedback
jmagly/aiwg 107
-
pipeline-design
Interactive LLM inference pipeline design — elicits requirements, recommends pattern, scaffolds production-ready artifacts
jmagly/aiwg 107
-
cost-optimizer
Analyze LLM pipeline costs and generate concrete optimization recommendations with savings estimates
jmagly/aiwg 107
-
pipeline-status
Show status overview of all LLM inference pipelines in the current project
jmagly/aiwg 107
-
iteration-control
jmagly/aiwg 107
-
devkit-create-extension
Create a new AIWG extension (framework expansion pack) with AI-guided setup
jmagly/aiwg 107
-
link-check
Verify @file references in AIWG skills and agents against the linking contract — per-file or corpus-wide, with optional auto-fix
jmagly/aiwg 107
-
validate-component
Validate a single AIWG component (skill, agent, or command) for completeness and correctness
jmagly/aiwg 107
-
devkit-create-framework
Comma-separated phase names
jmagly/aiwg 107
-
devkit-create-addon
Create a new AIWG addon with AI-guided setup
jmagly/aiwg 107