foundry
Foundry development guide for CMTAT RuleEngine contracts, including testing, deployment scripts, and project-specific Solidity patterns.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
545 skills found
Foundry development guide for CMTAT RuleEngine contracts, including testing, deployment scripts, and project-specific Solidity patterns.
Development and maintenance of the PWAFire library: build PWA API modules, handle feature detection, manage testing, and contribute to codebase following strict sync/async patterns and error handling requirements.
Create structured, orchestrator-ready project plans with atomic tasks, sprint structures, and validation criteria for multi-task engineering projects.
Discover and recommend combinations of agent skills to complete complex, multi-faceted tasks using Maximum Quality or Minimum Dependencies strategies.
Comprehensive Linux development environment management for compilers, build tools, IDEs, and debugging workflows.
Skill for managing MCP-based research, documentation lookups, and coordination between external search tools and plugin-backed memory systems.
End-to-end autonomous research agent: from idea generation and literature review to experiment execution, adversarial review loops, and paper writing.
Java development skill for writing clean, maintainable code using SOLID principles, pragmatic abstraction, and self-documenting practices.
Analyzes Claude Code chat history to identify coding patterns and skill gaps, curates personalized learning resources from HackerNews, and sends progress reports to Slack.
An automated memory middleware for AI agents, implementing a Retrieve-Respond-Save loop to maintain long-term persistent context across conversations.
Apply effective software quality consultancy practices. Use when consulting on QA strategy, advising development teams, or establishing sustainable quality workflows.
Python toolkit for mass spectrometry data processing. Enables spectral file importing (mzML, MGF, MSP), metadata harmonization, peak filtering, and calculating spectral similarity scores (cosine, modified cosine) for metabolomics.