183 skills ・ Official · GitHub Copilot · sorted by popularity
Extract lessons from corrections, praise, and unexpected cases in conversations. Organize findings by confidence level and propose updates to individual agent histories or shared team decisions, with changes shown for approval before saving.
Add checks to npm release workflows for version formats, authentication tokens, delayed package availability, and draft releases. The skill also covers preventing build scripts from unexpectedly changing release versions.
Document responses to GitHub pull request reviews by replying to each comment thread after fixes are pushed. Connect feedback to specific changes and commits, explain rejected suggestions, and selectively resolve automated review threads.
Keep tests aligned with API changes and actual project files. This skill guides agents to update related tests in the same commit, refresh expected counts and lists, and check stale assertions when automated checks fail.
Coordinate work across AI agents with shared rules for locating team files, recording decisions and their reasons, and requesting help. It also defines who owns revisions after a reviewer rejects an artifact.
Coordinate work across independent Squad installations by discovering their capabilities and delegating tasks across repositories. It guides context sharing, acceptance criteria, and progress tracking, while distinguishing persistent Squad teams from temporary groups of agents.
Learn how to start an AI team with Squad in Copilot CLI. This reference explains how to invoke the coordinator agent, find the command catalog, and initialize a new project while avoiding common invocation mistakes.
Follow Squad's Git workflow from issue branches through pull requests and cleanup. It covers development from dev, isolated directories for parallel issues, coordinated changes across repositories, and promotion to preview, insiders, and stable releases.
Adapt Squad agent coordination to the available Copilot interface. Detect supported tools, choose how to launch helper agents and collect results, and use file-based state for workflows that must work across interfaces.
Find and start common Squad operations through a categorized menu. The coordinator guides users through team management, GitHub issues, plugins, model settings, and session history, collecting required details and confirming changes where the catalog requires it.
Review git and gh operations in gh-aw workflows to check credential availability for each repository. Identify missing token handoffs, risky expansions of limited checkouts, and error handling needed where credentials are intentionally unavailable.
Use concrete JSON and Markdown examples to structure Sergo tool caches, strategy histories, improvement tasks, and reports. The templates show which fields to record and how to organize findings for review.
Improve validation errors in gh-aw so users can see what went wrong, what input is expected, and how to fix it. Provides writing patterns, valid YAML examples, Go error-handling guidance, and checks for message quality.
Implement and test Go codemods, automated migration routines used by gh aw fix. The guide covers targeted configuration changes, preserving comments and document content, safe repeated execution, and checks for registration and execution order.
Organize gh-aw Go code with guidance on splitting files by function, placing shared helpers, and keeping tests near implementations. It also explains string cleanup conventions and replacement implementations for features unavailable in WebAssembly builds.
Implement HTTP headers that pass GitHub Actions secrets through environment variables in gh-aw’s copilot engine. This reference explains secret extraction, generated MCP configuration, execution-step settings, and tests for keeping secret values out of configuration files.
Review GitHub security advisories, verify fixed versions, and update compatibility rules with narrowly scoped changes. Document upgrade steps and check that version blocking, warnings, and related configuration behave as intended.
Set up gh-aw, a GitHub CLI extension that turns Markdown workflows into GitHub Actions. The skill provides installation options and points agents to further instructions for creating, updating, debugging, and optimizing those workflows.
List GitHub Actions workflows with a script that lets you choose the page size and page number. Get JSON containing the total count, workflow names, file paths, states, timestamps, and links for inspection or further processing.
Inspect JSON files or API responses with jq and produce a compact map of keys and value types. Use the result to understand nested data before writing queries or processing the full dataset.
Analyze gh-aw execution traces, which record individual processing steps, to investigate slow or failing workflows. Using local JSONL files or telemetry backends, the skill checks timing, errors, missing attributes, and trace connections to support focused improvements.
Analyze token usage and AI costs in GitHub Agentic Workflows, identify expensive steps and budget or timeout failures, and develop prioritized improvements checked against the original workflow’s output quality.
Handle pull request review feedback by collecting comments, grouping requests, planning fixes, and validating changes before replying. The workflow covers team members and trusted GitHub automation, with individual replies and resolution of addressed discussion threads.
Retrieve labels from a GitHub repository, filter their names by partial matches, and choose page sizes and page numbers. Results arrive as JSON, including label names, colors, descriptions, and pagination details.