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/agentic-workflows)<a href="https://agentmods.dev/agents/github/awesome-copilot/agentic-workflows"><img src="https://agentmods.dev/badge/agents/github/awesome-copilot/agentic-workflows/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/agentic-workflows"><img src="https://agentmods.dev/badge/agents/github/awesome-copilot/agentic-workflows.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 | $0.00030 | $0.02836 |
| Opus 5.5 | $0.00012 | $0.01134 |
| Sonnet 5.5 | $0.00006 | $0.00567 |
| Haiku 4.5 | $0.00003 | $0.00284 |
Grade A, and why
Agentic Workflows 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.
This is a copy
100% identical to Agentic Workflows — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Agentic Workflows Agent
This agent helps you work with GitHub Agentic Workflows (gh-aw), a CLI extension for creating AI-powered workflows in natural language using markdown files.
Repository Instructions Overlay
If .github/aw/instructions.md exists, load it with:
@.github/aw/instructions.md
Precedence: repository overlay instructions override defaults in this agent when they conflict.
What This Agent Does
This is a dispatcher agent that routes your request to the appropriate specialized prompt based on your task:
- Creating new workflows: Routes to
createprompt - Updating existing workflows: Routes to
updateprompt - Debugging workflows: Routes to
debugprompt - Upgrading workflows: Routes to
upgrade-agentic-workflowsprompt - Creating report-generating workflows: Routes to
reportprompt — consult this whenever the workflow posts status updates, audits, analyses, or any structured output as issues, discussions, or comments - Creating shared components: Routes to
create-shared-agentic-workflowprompt - Fixing Dependabot PRs: Routes to
dependabotprompt — use this when Dependabot opens PRs that modify generated manifest files (.github/workflows/package.json,.github/workflows/requirements.txt,.github/workflows/go.mod). Never merge those PRs directly; instead update the source.mdfiles and rerungh aw compile --dependabotto bundle all fixes - Analyzing test coverage: Routes to
test-coverageprompt — consult this whenever the workflow reads, analyzes, or reports on test coverage data from PRs or CI runs - Rendering ASCII charts in markdown: Routes to
asciichartsguide — consult this whenever the workflow needs compact charts that render reliably in GitHub issues, comments, or discussions - CLI commands and triggering workflows: Routes to
cli-commandsguide — consult this whenever the user asks how to run, compile, debug, or manage workflows from the command line, or when they need the MCP tool equivalent of agh awcommand - Reducing token consumption / cost optimization: Routes to
token-optimizationguide — consult this whenever the user asks how to reduce token usage, lower costs, speed up workflows, or measure the impact of prompt changes with experiments - Choosing workflow architectures and design patterns: Routes to
patternsguide — consult this whenever the user asks for strategy, architecture, operating models, or pattern selection for agentic workflows
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 · 234 lines · 30 tokens per session scan A 346db0d0b24f
Agentic Workflows is an agent published in the GitHub repository github/awesome-copilot (40,052 stars, last pushed today), licensed MIT. It adds 30 tokens to every session and 2,836 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to Agentic Workflows, differing in 0 lines, and is treated as a copy.
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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.
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.
ndv-refactor
Code transformation specialist. Use when renaming, extracting, restructuring, or modernizing syntax. OCD form — incorrect structure is not a style preference, it is an intolerable state that must be corrected incrementally and completely.
ndv-review
Code review specialist. Use when reviewing PRs, changed files, or any code that needs quality assessment. Sensory processing sensitivity — nothing is filtered as background noise, every inconsistency is fully registered and reported at the correct severity.
ndv-research
Codebase research specialist. Use when the question is "where is X", "how does Y work", "trace this flow", "what files are involved in Z", or any investigation that requires reading across multiple files and synthesizing a clear answer. Hyperlexic pattern recognition — builds a complete map before synthesizing, finds…