Discover Testing & security skills, compare source repositories and read the instructions for each workflow.
Deep competitive intelligence combining web scraping, LinkedIn data, social media monitoring, leadership analysis, GitHub activity, Glassdoor sentiment, and community insights. Analyzes founders/C-level profile...
Deep multi-platform intelligence analysis combining LinkedIn (profile, posts, activity), Twitter/X (tweets, engagement), Reddit (discussions, community), web presence (articles, GitHub, blogs), and company inte...
Deep multi-platform intelligence search across ALL AnySite MCP sources (LinkedIn, Twitter, Instagram, Reddit, Y Combinator, web). Auto-detects search type (person, company, or topic) and performs CASCADING rese...
Universal VC investor analysis and outreach agent. Analyzes any startup project, understands fundraising stage, identifies ideal investor profile, scores investors, detects portfolio conflicts, generates person...
Build and refine Ideal Customer Profiles (ICP) using real LinkedIn data via AnySite MCP. Analyzes existing customers, identifies patterns, generates scoring criteria, and finds lookalike prospects. Use when use...
deploy the Wasp app to Railway or Fly.io using Wasp CLI.
Start the Wasp dev server and set up full debugging visibility. This includes running the server (with access to logs), and connecting browser console access so Claude can see client-side errors. Essential for...
Add Wasp's built-in features to your app — auth, email, jobs, and more. These are full-stack, batteries-included features that Wasp handles for you. Use when the user wants to add meta tags, authentication (ema...
Shows the Wasp plugin's available features, commands, and skills.
Guide for quality focused software architecture. This skill should be used when users want to write code, design architecture, analyze code, in any case that relates to software development.
used when maintaining UT
Use to maintain context across sessions - integrates episodic-memory for conversation recall and mcp__memory knowledge graph for persistent facts
Setup Sentry Tracing (Performance Monitoring) in any project. Use this when asked to add performance monitoring, enable tracing, track transactions/spans, or instrument application performance. Supports JavaScr...
Use when documentation drift is detected. Comprehensively audits codebase and creates/updates Swagger, features docs, and general documentation to achieve full sync.
Use for LARGE work requiring feature-level grouping. Creates epic tracking issues, manages related issues under a common label, tracks epic progress, and coordinates with milestones.
Use for time-based grouping of issues into delivery phases. Creates, updates, and tracks milestones, associates issues and epics, monitors progress toward milestone completion.
Source royalty-free images and videos from Pexels API for design, placeholders, or content. Supports search, curated/popular content, collections, multiple resolutions, and ALWAYS creates detailed sidecar metad...
Use after creating PR - monitor CI pipeline, resolve failures, address review feedback, and merge when all gates pass
Use before starting implementation - research repository documentation, codebase patterns, and external resources to inform the approach
Use at the beginning of every work session - establishes context by checking GitHub project state, reading memory, verifying environment, and orienting before starting work
Use after completing implementation - create pull request with complete documentation, proper labels, linked issues, and verification summary
Defines behavior protocol for spawned worker agents. Injected into worker prompts. Covers startup, progress reporting, exit conditions, and handover preparation.
Use before code review - determine if change is minor (review new code only) or major (review impacted code too)
Defines context handover format when workers hit turn limit. Posts structured handover to GitHub issue comments enabling replacement workers to continue seamlessly.
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.