problem-mapping
Structured problem-framing tool for design sprints and product strategy. Facilitates collaborative or individual sessions to define goals, stakeholders, constraints, and pain points before solution generation.
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376 skills found
Structured problem-framing tool for design sprints and product strategy. Facilitates collaborative or individual sessions to define goals, stakeholders, constraints, and pain points before solution generation.
Automated quality gate using 5 parallel AI agents to review code changes for correctness, style, and consistency.
Conduct thorough dependency audits to identify redundant code, unused features, and improper usage patterns. Ensures project modularity by leveraging existing dependencies instead of reinventing functionality.
A robust verification and QA system for software agents featuring real-time truth scoring, automated code validation, and instant rollback capabilities to maintain high reliability.
High-performance Solana meme coin trading for AI agents: sniping, MEV-protected execution, rug detection, and automated position management.
Build and manage MCP servers using the FastMCP framework. Guide for creating tools, resources, prompts, Claude Desktop integration, and deployment with Python and TypeScript.
Detects indirect prompt injection and goal hijacking in AI agents by evaluating how they process external content like RAG, documents, and web data.
Base ecosystem skill for Refly. Creates, discovers, and runs domain-specific skills, routes user intent to workflows via symlinks, and automates multi-step pipelines via the Refly CLI.
Enforce high-quality testing practices by identifying and preventing common anti-patterns like mock-testing, test-only production code, and incomplete dependency mocking.
Diagnose, isolate, and mitigate LLM context failures like lost-in-middle, poisoning, distraction, and context clash to improve agent reliability.
A structured decision-making tool that applies RICE, MoSCoW, Kano, and value-effort frameworks to prioritize software features, roadmap items, and build-vs-defer decisions with data-driven objectivity.
Deploy specialized AI swarms to perform comprehensive, multi-domain GitHub pull request reviews covering security, performance, architecture, and style.