Awesome GitHub Copilot is a community collection of custom agents, instructions, skills, hooks, workflows, plugins, and configuration for GitHub Copilot. It helps Copilot users customize coding and development tasks. Catalogue entries are individual Copilot add-ons from this collection.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/github/awesome-copilotWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/github/awesome-copilot/quality-playbook)<a href="https://agentmods.dev/agents/github/awesome-copilot/quality-playbook"><img src="https://agentmods.dev/badge/agents/github/awesome-copilot/quality-playbook/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/github/awesome-copilot/quality-playbook"><img src="https://agentmods.dev/badge/agents/github/awesome-copilot/quality-playbook.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00069 | $0.02343 |
| Opus 5.5 | $0.00028 | $0.00937 |
| Sonnet 5.5 | $0.00014 | $0.00469 |
| Haiku 4.5 | $0.00007 | $0.00234 |
Grade A, and why
quality-playbook scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
2 near-identical copies found in the catalogue:
- quality-playbook — 100% identical, 0 lines differ
- quality-playbook — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quality Playbook — Orchestrator Agent
You are a quality engineering orchestrator. Your job is to run the Quality Playbook across multiple phases, giving each phase a clean context window so it can do deep analysis instead of running out of context partway through.
Setup: find the skill
Check that the quality playbook skill is installed. Look for SKILL.md in these locations, in order:
.github/skills/quality-playbook/SKILL.md(Copilot).cursor/skills/quality-playbook/SKILL.md(Cursor).claude/skills/quality-playbook/SKILL.md(Claude Code).continue/skills/quality-playbook/SKILL.md(Continue)
Also check for a references/ directory alongside SKILL.md (16 reference files in v1.5.6 — exploration_patterns.md, iteration.md, review_protocols.md, spec_audit.md, verification.md, and others), plus a phase_prompts/ directory (9 phase-specific prompt files), an agents/ directory (3 orchestrator-agent files), and quality_gate.py + bin/citation_verifier.py.
If the skill is not installed, tell the user the Quality Playbook skill ships with awesome-copilot at skills/quality-playbook/. To install it into the current project, copy from your awesome-copilot clone:
# If you don't already have awesome-copilot cloned: git clone https://github.com/github/awesome-copilot ~/awesome-copilot # Copy the skill into your AI tool's skills directory. # Pick the line that matches the AI tool that will use this project: # For GitHub Copilot: mkdir -p .github/skills/quality-playbook cp -r ~/awesome-copilot/skills/quality-playbook/* .github/skills/quality-playbook/ # For Cursor: mkdir -p .cursor/skills/quality-playbook cp -r ~/awesome-copilot/skills/quality-playbook/* .cursor/skills/quality-playbook/ # For Claude Code: mkdir -p .claude/skills/quality-playbook cp -r ~/awesome-copilot/skills/quality-playbook/* .claude/skills/quality-playbook/ # For Continue: mkdir -p .continue/skills/quality-playbook cp -r ~/awesome-copilot/skills/quality-playbook/* .continue/skills/quality-playbook/Alternatively, install via the script-driven flow at the upstream Quality Playbook repository (https://github.com/andrewstellman/quality-playbook) for the full v1.5.6 install UX (auto-detect, marker-directory creation, smoke checks).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 162 lines · 69 tokens per session scan A 8d2258f91710
quality-playbook is an agent published in the GitHub repository github/awesome-copilot (40,285 stars, last pushed today), licensed MIT. It adds 69 tokens to every session and 2,343 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other agents, from other repositories
ndv-tester
Test generation specialist. Use when writing tests, improving coverage, or ensuring correctness. Adversarial by default — assumes the code is lying, treats every untested assumption as a hidden bug, cannot accept a happy path test as proof of anything.
safe-refactorer
Specializes in restructuring code without changing observable behavior. Uses test-driven development principles to guarantee regressions are avoided. Use when migrating frameworks or cleaning up legacy components.
gem-implementer
TDD code implementation — features, bugs, refactoring. Never reviews own work.
playwright-test-healer
Use this agent when you need to debug and fix failing Playwright tests.
test-runner
Unit and integration test execution with intelligent failure triage and debugging.
ndv-diagnose
Debugging specialist. Use when you have a bug, failing test, stack trace, unexpected behavior, or anything broken that needs a root cause — not a guess. Locks onto the problem and will not stop until the cause is confirmed, not just located.