memory-checkpoint
Memory Checkpoint is an AI agent skill that streamlines biomedical literature research by providing a professional MCP server with 40 tools, multi-source search, and full-text access, benefiting developers and researchers.
Explora e instala miles de habilidades para AI Agents en el directorio de Killer-Skills. Compatible con Claude Code, Windsurf, Cursor y más.
Memory Checkpoint is an AI agent skill that streamlines biomedical literature research by providing a professional MCP server with 40 tools, multi-source search, and full-text access, benefiting developers and researchers.
ArcticDB is a high performance, serverless DataFrame database built for the Python Data Science ecosystem.
Audit codebase files against the 4-pillar quality manifesto using RECON work batches, with batch processing and context budget management (Titan Paradigm Phase 2)
The laravel-verification skill automates environment checks, linting, static analysis, tests, and security scans for Laravel projects, benefiting developers by ensuring deployment readiness and security.
Investigación profunda es una función que utiliza firecrawl y exa MCP para producir informes de investigación exhaustivos.
Business Analyst (Atlas). Use for market research, competitive analysis, user research, brainstorming session facilitation, structured ideation workshops, feasibility studies, i...
Business Analyst (Atlas). Use for market research, competitive analysis, user research, brainstorming session facilitation, structured ideation workshops, feasibility studies, i...
Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations with vLLM/lighteval. Works with the model-index metadata format.
Use the CRISP‑T MCP server to run a full qualitative analysis workflow linking textual narratives and numeric data.
Conduct market research, competitive analysis, and industry intelligence. Use when the user wants market sizing, competitor comparisons, OSS landscape scans, distribution analysis, or research that informs build-or-skip decisions.
Guide to implement rigorous validation layers including static analysis, automated testing, structured logging, and security scanning.
Evaluate product desirability, market positioning, and emotional resonance—the complement to friction analysis. Assess whether users will WANT a product (not just use it), identity fit, trust