qa-api-testing-contracts
API contract testing across REST, GraphQL, and gRPC. Use when you need schema validation, breaking-change detection, and CI quality gates.
qa-debugging
Systematic debugging for crashes, regressions, flakes, and production bugs. Use when diagnosing stack traces, logs, traces, or profiling data.
ai-ml-timeseries
Time series forecasting — LightGBM, Transformers, temporal validation, feature engineering, and production deployment. Use when building TS models.
qa-docs-coverage
Audit and enforce doc quality. Use when checking coverage, freshness, runbook validity, or cleaning stale/duplicate markdown after LLM edits.
software-ux-research
Covers user research methods and research ops. Use when running interviews, usability tests, surveys, or A/B tests to de-risk product decisions.
ai-rag
RAG and search engineering — chunking, hybrid retrieval, reranking, and nDCG evaluation. Use when building retrieval-augmented generation pipelines.
mini-wiki
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payload
Use when working with Payload projects (payload.config.ts, collections, fields, hooks, access control, Payload API). Use when debugging validation errors, security issues, relationship queries, transactions, or hook behavior.
quiz-generator
This skill generates interactive multiple-choice quizzes for each chapter of an intelligent textbook, with questions aligned to specific concepts from the learning graph and distributed across Bloom's Taxonomy cognitive levels to assess student understanding effectively. Use this skill after chapter content has been written and the learning graph exists.
story-generator
This skill generates graphic novel narratives about physicists and scientists for intelligent textbooks. It creates compelling, historically-accurate stories with image prompts designed for high school students. Use this skill when the user wants to add a new scientist story to the Physics History Graphic Novels section of an MkDocs Material textbook, or when creating educational graphic novel content about historical scientists.
reference-generator
This skill generates curated, high-quality reference lists for textbooks with 10 references per chapter. References prioritize Wikipedia for reliability, include detailed relevance descriptions, and are stored in separate references.md files for token efficiency. Use this skill when working with intelligent textbooks that need academic references.
book-installer
Installs and configures project infrastructure including MkDocs Material intelligent textbook templates, learning graph viewers, and skill tracking systems. Routes to the appropriate installation guide based on what the user needs to set up.
chapter-content-generator
This skill generates comprehensive chapter content for intelligent textbooks after the book-chapter-generator skill has created the chapter structure. Use this skill when a chapter index.md file exists with title, summary, and concept list, and detailed educational content needs to be generated at the appropriate reading level with rich non-text elements including diagrams, infographics, and MicroSims. (project, gitignored)
readme-generator
This skill creates or updates a README.md file in the GitHub home directory of the current project. The README.md file it generates will conform to GitHub best practices, including badges, project overview, site metrics, getting started instructions, and comprehensive documentation.
course-description-analyzer
This skill analyzes or creates course descriptions for intelligent textbooks by checking for completeness of required elements (title, audience, prerequisites, topics, Bloom's Taxonomy outcomes) and providing quality scores with improvement suggestions. Use this skill when working with course descriptions in /docs/course-description.md that need validation or creation for learning graph generation.
diagram-reports-generator
This skill generates comprehensive diagram and MicroSim reports for the geometry course by analyzing chapter markdown files and creating table and detail reports. Use this skill when working with an intelligent textbook (specifically geometry-course) that needs updated visualization of all diagrams and MicroSims across chapters, including their status, difficulty, Bloom's Taxonomy levels, and UI complexity.
glossary-generator
This skill automatically generates a comprehensive glossary of terms from a learning graph's concept list, ensuring each definition follows ISO 11179 metadata registry standards (precise, concise, distinct, non-circular, and free of business rules). Use this skill when creating a glossary for an intelligent textbook after the learning graph concept list has been finalized.
linkedin-announcement-generator
This skill generates professional LinkedIn announcement text for intelligent textbooks by analyzing book metrics, chapter content, and learning resources to create engaging posts with key statistics, hashtags, and links to the published site. Use this skill when you need to create social media announcements about textbook completion or major milestones.
moving-rainbow
Generate MicroPython programs for the Moving Rainbow LED strip educational project using Raspberry Pi Pico with NeoPixel strips and button controls.
microsim-generator
Creates interactive educational MicroSims using the best-matched JavaScript library (p5.js, Chart.js, Plotly, Mermaid, vis-network, vis-timeline, Leaflet, Venn.js). Analyzes user requirements to route to the appropriate visualization type and generates complete MicroSim packages with HTML, JavaScript, CSS, documentation, screen capture, and metadata.
book-metrics-generator
This skill generates comprehensive metrics reports for intelligent textbooks built with MkDocs Material, analyzing chapters, concepts, glossary terms, FAQs, quiz questions, diagrams, equations, MicroSims, word counts, and links. Use this skill when working with an intelligent textbook project that needs quantitative analysis of its content, typically after significant content development or for project status reporting. The skill creates two markdown files - book-metrics.md with overall statistics and chapter-metrics.md with per-chapter breakdowns - in the docs/learning-graph/ directory.
book-chapter-generator
This skill generates a structured chapter outline for intelligent textbooks by analyzing course descriptions, learning graphs, and concept dependencies. Use this skill after the learning graph has been created and before generating chapter content, to design an optimal chapter structure that respects concept dependencies and distributes content evenly across all of the chapter in a book.
microsim-utils
Utility tools for MicroSim management including quality validation, screenshot capture, icon management, and index page generation. Routes to the appropriate utility based on the task needed.
faq-generator
This skill generates a comprehensive set of Frequently Asked Questions (FAQs) from the course description, course content, learning graphs, concept lists, MicroSims, and glossary terms to help students understand common questions and prepare content for chatbot integration. Use this skill after course description, learning graph, glossary, and at least 30% of chapter content exist.
learning-graph-generator
Generates a comprehensive learning graph from a course description, including 200 concepts with dependencies, taxonomy categorization, and quality validation reports. Use this when the user wants to create a structured knowledge graph for educational content.
Linear
Managing Linear issues, projects, and teams. Use when working with Linear tasks, creating issues, updating status, querying projects, or managing team workflows.
zimage-skill
Generate images using ModelScope Z-Image-Turbo API. Use when user asks to generate, create, or make images, pictures, or illustrations.
domain-assessment
Domain reconnaissance coordinator that orchestrates subdomain discovery and port scanning to build comprehensive domain attack surface inventory
common-appsec-patterns
Application security testing coordinator for common vulnerability patterns including XSS, injection flaws, and client-side security issues. Orchestrates specialized testing agents to identify and validate common application security weaknesses.
authenticating
Authentication testing skill - automates signup, login, 2FA bypass, CAPTCHA solving, and bot detection evasion using Playwright MCP. Tests authentication security controls. Includes behavioral biometrics simulation, OTP handling, and automated account creation for security assessments.
ai-threat-testing
Offensive AI security testing and exploitation framework. Systematically tests LLM applications for OWASP Top 10 vulnerabilities including prompt injection, model extraction, data poisoning, and supply chain attacks. Integrates with pentest workflows to discover and exploit AI-specific threats.
pentest
Penetration testing orchestrator that coordinates specialized attack agents. Provides attack indexes, methodology frameworks, and documentation. Execution delegated to specialized agents (SQL Injection, XSS, SSRF, etc.). Use for engagement planning and attack coordination.
web-application-mapping
Comprehensive web application reconnaissance and mapping coordinator that orchestrates passive browsing, active endpoint discovery, attack surface analysis, and headless browser automation for complete application coverage.
hackerone
HackerOne bug bounty automation - parses scope CSVs, deploys parallel pentesting agents for each asset, validates PoCs, and generates platform-ready submission reports. Use when testing HackerOne programs or preparing professional vulnerability submissions.
cve-testing
CVE vulnerability testing coordinator that identifies technology stacks, researches known vulnerabilities, and tests applications for exploitable CVEs using public exploits and proof-of-concept code.
ip-attribution
Maps IP addresses to cloud providers, ASNs, and organizations via WHOIS
javascript-dom-analysis
Detects frontend frameworks via global variables, DOM attributes, and bundle patterns
job-posting-analysis
Extracts technology requirements from job postings and career pages
api-portal-discovery
Discovers public API portals, developer docs, and OpenAPI/Swagger endpoints
backend-inferencer
Infers backend technologies including servers, languages, frameworks, databases, and CMS
cdn-waf-fingerprinter
Identifies CDNs (Cloudflare, Akamai, Fastly) and WAFs
certificate-transparency
Queries CT logs for certificates and extracts SANs for subdomain discovery
cloud-infra-detector
Detects cloud providers (AWS, Azure, GCP) and PaaS platforms
code-repository-intel
Scans GitHub/GitLab for public repos, dependencies, and CI configurations
devops-detector
Detects CI/CD tools, containerization, and orchestration from public signals
dns-intelligence
Extracts technology signals from DNS records (MX, TXT, NS, CNAME, SRV)
domain-discovery
Discovers official company domain via web search, WHOIS, and common TLD patterns
frontend-inferencer
Infers frontend technologies including React, Angular, Vue, jQuery, Bootstrap, etc.
tls-certificate-analysis
Analyzes TLS certificates for issuer, SAN, and JARM fingerprints
web-archive-analysis
Uses Wayback Machine to detect technology migrations over time
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