Coding standards, frameworks, refactoring, and code review (15.8K skills)
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.
Explains how Squad CLI records its installed version and handles upgrades, including which files it replaces or preserves. It also covers checking npm release channels and using cached version information when assessing available updates.
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.
Set up an AI agent team by proposing roles and names for a project, then creating shared team files after confirmation. Initialize member context, decision records, and logs so the team starts with a common project background.
Consult Squad’s file ownership and authority rules to decide where state belongs, who may read or write it, and which source takes precedence. Distinguish authoritative configuration from append-only histories and reference material.
Coordinate independent Squad AI teams across repositories using procedures for questions, review requests, and task delegation. Choose between direct CLI sessions, reading team metadata, and asynchronous requests based on repository access and task needs.
Capture interface or documentation pages with Playwright and embed the screenshots in a GitHub pull request description. Reviewers can inspect visual changes without checking out the branch, using images hosted on a temporary branch.
Set up separate commands for personal and work GitHub accounts on Windows. Detects accounts already signed in through GitHub CLI, asks which serves each role, creates PowerShell shortcuts and CMD wrappers, and verifies the selected usernames.
Find and select Squad operations through a categorized menu, from managing an AI team and GitHub issues to choosing models and reviewing activity. The skill collects required options and routes requests to CLI commands or the coordinator agent.
Document project-specific development rules for an AI agent using a starter template. It provides sections for error handling, testing, code style, file organization, examples, and practices to avoid, ready to fill with actual conventions.
Set up a Squad agent team in a repository that has no team yet. Propose roles and persistent names, obtain user confirmation, then create team files, shared context, built-in member policies, and merge settings for accumulated records.
Reduce GitHub API calls during issue monitoring by scanning basic issue details first, then fetching full descriptions and comments only for selected issues. Filters use assignees, status labels, and title patterns to narrow the list.
Apply Squad SDK and CLI versioning rules to keep package versions aligned and development-only versions out of shared branches. It explains how prerelease versions affect npm workspace dependencies and defines release ownership and CI checks.
Extend safe-output jobs, which execute agent-generated actions, to reference newly created issues through temporary IDs. The guide covers job dependencies, issue-number resolution, input validation, tests, and warning-based handling of unresolved references.
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.
Define and check GitHub Copilot instructions and specialized agents using Markdown files. It explains file locations, configuration fields, tool access, path-specific rules, and workflow integration, with examples for documentation, testing, reviews, and other development tasks.
Follow gh-aw development conventions with checks matched to Go, JavaScript, and workflow changes. Provides staged validation commands, capitalization rules, and pointers to more detailed guidance for specific parts of the codebase.
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.
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.
Guide gh-aw release preparation and assess whether command-line changes break existing usage. The reference covers changesets, which record release changes, version previews, release steps, firewall log classification, and summaries of Go module usage.
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.
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.
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.