488 skills (repositories by github) · sorted by popularity
Use this reference to configure GitHub access for AI agents through MCP, a protocol for connecting agents to tools. Covers tool selection, authentication, read-only access, and migration of existing workflow settings.
Design error recovery for gh-aw workflows, including failed installations and API calls. Define retry limits, increasing wait times, error categories, and debug logs to handle temporary failures and prevent endless retries.
Guide changes to gh-aw internals, including workflow validation, session scoring, and GitHub output handling. Find implementation locations and design rules for configuration checks, YAML compatibility, and limits on log responses returned to agents.
Helps agents work within gh-aw tool restrictions by checking the allowlist, diagnosing denied calls, and choosing permitted alternatives. It guides agents to complete available work and report specific limitations before repeated denials end the session.
Build and troubleshoot canvas extensions displayed in the GitHub Copilot app's side panel. Follow guidance for scaffolding, implementing actions and inputs, preserving state, matching app themes, and checking behavior through canvas tools and extension logs.
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.
Resolve merge conflicts in generated workflow lock files by rebuilding them from merged Markdown sources. The skill checks for leftover conflict markers, stages regenerated files, and verifies that unresolved paths and whitespace errors are cleared.
Write JavaScript for actions/github-script@v8 in GitHub Actions. Apply consistent logging, pass outputs and environment variables to later steps, publish readable summaries, and handle errors with the action's provided utilities.
Format gh-aw terminal output using Go struct tags, annotations attached to data fields. Set labels and section titles, format numbers and dollar amounts, omit empty fields, and render lists of records as tables.
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.
Query GitHub pull requests by author, status, or review needs, and extract selected fields as JSON. Inspect the data structure and size first, then use jq, a JSON filtering tool, to refine results.
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.
Publish gh-aw changes as a draft pull request from a GitHub Copilot cloud agent. The workflow checks repository templates, runs required local validation, commits and pushes through runtime tools, and records the validation results in the PR.
Design metrics that measure whether a workflow achieved its intended outcome using recorded session evidence. Choose built-in checks or custom JavaScript, retain suitable Bash evaluators, and define tests that distinguish success, failure, and missing evidence.
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.
Review regular expressions used to detect errors in agent engines. Check for empty matches, test patterns against real logs, and add safeguards against repeated matches that can cause JavaScript loops to hang.
Add an agent execution engine to gh-aw using a shared Markdown definition where possible. The skill guides installation, authentication, configuration, and testing, with Go infrastructure changes reserved for capabilities that existing settings cannot express.
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.
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.
Turn a code pattern fixed in a pull request into a custom Go linter, a tool that checks code without running it. Covers a focused detection rule, tests, and registration in the linter runner.
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.
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.
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.
Query GitHub Discussions and extract titles, authors, categories, or answer status. First inspect the data structure and size, then use jq, a JSON filtering tool, to select relevant discussions, sort updates, or count entries by category.