Claude Skills by github

Publish validated gh-aw changes as a draft pull request from a cloud agent.

Design and verify a deterministic operational-value grader for a GitHub Agentic Workflow. Use for per-run operational value, evidence attribution, maturation, baselines, and operational-value evaluators. Usage: /operational-value-designer OWNER/REPO WORKFLOW-NAME.

Analyze and reduce token consumption in agentic workflows — guardrail-specific entry points, measurement, and optimization techniques.

Prepare an open pull request for merge from a GitHub Copilot cloud agent. Drives Reviews, local validation, and Mergeable to a ready state. Does not merge, and cannot trigger CI.

Rewrite prompts for minimal tokens, maximal clarity, and low ambiguity for LLM consumption.

Format reports with HTML details/summary blocks for readable output.

Merge a base ref and safely regenerate compiled workflow lock-file conflicts.

Operate safely and efficiently inside a gh-aw workflow with a restricted tools/bash allowlist, and correctly triage tool-denial events before they exhaust the session's denial budget.

Review agentic workflow changes for correctness, security posture, and optimization opportunities with compile, validation, and audit evidence.

Review a GitHub security advisory and safely update .github/aw/compat.json with evidence-backed version enforcement.

Optional Sergo examples for cache formats and reporting templates.

Run and integrate Skillz MCP server with Docker for skill execution.

Add temporary ID support to safe-output jobs end to end.

Write clear GitHub Actions step summaries with progressive disclosure.

{what this skill teaches agents}

Standard collaboration patterns for all squad agents — worktree awareness, decisions, cross-agent communication

Shared hard rules enforced across all squad agents

How to write comprehensive architectural proposals that drive alignment before code is written

Defensive CI/CD patterns: semver validation, token checks, retry logic, draft detection — earned from v0.8.22

**Bug class:** Commands implemented in `packages/squad-cli/src/cli/commands/` but never routed in `cli-entry.ts`.

Platform detection and adaptive spawning for CLI vs VS Code vs other surfaces

The complete two-phase Init Mode protocol the Squad coordinator runs when no team exists yet in the current repo. Phase 1 = propose the team (no files created, wait for user confirm). Phase 2 = create .squad/ scaffolding, casting state, .gitattributes for merge drivers, and the always-on built-ins (Scribe, Ralph, Rai, Fact Checker). Loaded on demand when the coordinator detects no .squad/team.md exists.

Selecting WHO handles work is the Routing table; selecting HOW they handle it (Direct, Lightweight, Standard, Full) is Response Mode. This skill contains the complete decision table, exemplar prompts for each mode, the Lightweight spawn template, and the upgrade rules. Squad coordinator loads this on demand once routing has identified the agent — to pick the right ceremony level for the task.

The complete file-by-file source-of-truth hierarchy for Squad: which files are authoritative, which are derived/append-only, who may write each one, who may read each one, and the precedence rules when they conflict. Squad coordinator loads this on demand when it needs to resolve a write conflict, decide where a piece of state belongs, or answer a 'who owns this file' question.

Enables squad agents on different machines to share work via git-based task queuing

Protocol for sending queries, delegating tasks, and sharing context between independent Squad instances across different repositories

Coordinating work across multiple Squad instances — discovery, delegation, and disambiguation when the user says 'squad' (the product) vs casual English 'group of agents'.

How to coordinate with squads on different machines using git as transport

Microsoft Style Guide + Squad-specific documentation patterns

End-to-end validation of coordinator and agent template changes

Shifts Layer 3 model selection to cost-optimized alternatives when economy mode is active.

Standard recovery patterns for all squad agents. When something fails, adapt — don't just report the failure.

PAO workflow for scanning, drafting, and presenting community responses with human review gate

Review and validate claims using counter-hypothesis testing. Use when verifying technical content, checking references, validating API endpoints, or performing quality assurance on deliverables.

Safely manage multiple GitHub identities (EMU + personal) in agent workflows

Squad branching model: dev-first workflow with insiders preview channel

Detect and set up account-locked gh aliases for multi-account GitHub. The AI reads this skill, detects accounts, asks the user which is personal/work, and runs the setup automatically.

Record final outcomes to history.md, not intermediate requests or reversed decisions

Tone enforcement patterns for external-facing community responses

Team initialization flow (Phase 1 proposal + Phase 2 creation)

Max-3-cycle protocol for agent sub-tasks with WHY context and coordinator validation. Use when spawning sub-agents to complete scoped work.

Determines which LLM model to use for each agent spawn

Context hygiene — compress, prune, archive .squad/ state

Route agent notifications to specific channels by type — prevent alert fatigue from single-channel flooding

User-level AI agents that travel with you across projects

Teaches agents to reply to PR review comment threads after fixing issues, making resolutions traceable

Capture Playwright screenshots and embed them in GitHub PR descriptions

Core conventions and patterns for this codebase

Cuts GitHub API calls by separating lightweight list scanning from full hydration

Learning capture system that extracts HIGH/MED/LOW confidence patterns from conversations to prevent repeating mistakes. Use after user corrections ("no", "wrong"), praise ("perfect", "exactly"), or when discovering edge cases. Complements .squad/agents/{agent}/history.md and .squad/decisions.md.