github-copilot-agent-tips-and-tricks
Guidance and operational tips for identifying, reviewing, and managing pull requests created by the GitHub Copilot coding agent within your repository.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
226 skills found
Guidance and operational tips for identifying, reviewing, and managing pull requests created by the GitHub Copilot coding agent within your repository.
Automated academic literature retrieval, structured summarization, and multi-channel scheduling workflow for research topics.
Guide for installing or reimaging NixOS from live media using a declarative, flake-based approach with hardware-specific configuration support.
Intelligent GitHub release orchestration using AI swarms for automated versioning, multi-platform deployment, testing, and rollback management.
Accelerate software delivery by shifting testing to the earliest development phases, using AI-driven requirements validation, TDD, and automated CI pipelines to reduce defect costs.
MPC-based multi-chain wallet SDK and CLI for AI agents and developers. Perform secure, threshold-signed crypto operations (send, swap, sign) across 40+ blockchains without seed phrases.
Automates Moonwell protocol governance proposal lifecycle, from creation and verification to deployment and testing.
Cross-agent interaction skill via ANP protocol. Use decentralized identity (DID) to discover and invoke remote agents like maps, booking, and logistics services across the ANP network.
A secure Git commit workflow agent that prevents accidental mass commits and promotes surgical, file-specific staging and semantic commits.
Manages complete plugin lifecycle for JUCE development: install, uninstall, reset, and destroy. Handles system folder deployment, cache management, and safe, version-controlled removal for audio developers.
Streamline continuous fuzzing for open-source projects using the OSS-Fuzz CLI framework to build harnesses, manage configurations, and generate coverage reports.
Prevents AI hallucination and ensures evidence-based, verifiable outputs when analyzing code, reviewing technical documents, or providing recommendations.