Scrape documentation websites into organized reference files. Use when converting docs sites to searchable references or building Claude skills.
Skills in this repository
jmagly/aiwg - Page 14
SkillsMP has collected 552 skills from jmagly/aiwg. Open a skill to review its source and details.
jmagly/aiwgShowing 32 of 552 collected 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.
Read and parse an OpenProse program file, extracting its contract (requires, ensures, strategies, errors, invariants) and services into a structured representation
Clone or update the OpenProse repository to ensure AIWG prose tools hook into the latest version of the specification and examples
Validate an OpenProse program file against Prose contract grammar without executing it — checks frontmatter, contract structure, service references, and strategy syntax
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.
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.
Detect orphaned tests, obsolete assertions, and test-code misalignment. Use for test suite maintenance, cleanup, and traceability validation.
Detect requests for UAT generation, execution, or reporting and invoke the appropriate UAT command
Interactive tuning of Verbalized Sampling diversity parameters with preset management and A/B comparison
AWS, Azure, and GCP forensic investigation covering audit logs, IAM review, storage access, network flows, and compute instance forensics
Chain of custody and evidence preservation procedures covering log collection, hash verification, custody documentation, and evidence packaging per RFC 3227
Extract, classify, deduplicate, and enrich IOCs from investigation artifacts; map to STIX 2.1 observables
Generalized Linux incident response and forensic analysis covering Debian/Ubuntu, RHEL/CentOS/Rocky, and SUSE families
Volatility 3 memory forensics workflows covering acquisition with LiME and WinPmem, and structured analysis using Volatility 3 plugin reference
Apply Sigma rules against log sources for threat hunting; convert rules to Elasticsearch, Splunk, and grep queries
SBOM analysis, build pipeline forensics, and dependency verification covering package integrity, build reproducibility, and CI/CD pipeline tampering
Research and build a target system profile via SSH — discovers OS, services, users, network baseline, and security stack
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.