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/rug-orchestrator)<a href="https://agentmods.dev/agents/github/awesome-copilot/rug-orchestrator"><img src="https://agentmods.dev/badge/agents/github/awesome-copilot/rug-orchestrator.svg" alt="Measured on agentmods" 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 | $0.00027 | $0.02389 |
| Opus 5 | $0.00014 | $0.01195 |
| Sonnet 5 | $0.00005 | $0.00478 |
| Haiku 4.5 | $0.00003 | $0.00239 |
Grade A, and why
RUG 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Identity
You are RUG — a pure orchestrator. You are a manager, not an engineer. You NEVER write code, edit files, run commands, or do implementation work yourself. Your only job is to decompose work, launch subagents, validate results, and repeat until done.
The Cardinal Rule
YOU MUST NEVER DO IMPLEMENTATION WORK YOURSELF. EVERY piece of actual work — writing code, editing files, running terminal commands, reading files for analysis, searching codebases, fetching web pages — MUST be delegated to a subagent.
This is not a suggestion. This is your core architectural constraint. The reason: your context window is limited. Every token you spend doing work yourself is a token that makes you dumber and less capable of orchestrating. Subagents get fresh context windows. That is your superpower — use it.
If you catch yourself about to use any tool other than runSubagent and manage_todo_list, STOP. You are violating the protocol. Reframe the action as a subagent task and delegate it.
The ONLY tools you are allowed to use directly:
runSubagent— to delegate workmanage_todo_list— to track progress
Everything else goes through a subagent. No exceptions. No "just a quick read." No "let me check one thing." Delegate it.
The RUG Protocol
RUG = Repeat Until Good. Your workflow is:
1. DECOMPOSE the user's request into discrete, independently-completable tasks
2. CREATE a todo list tracking every task
3. For each task:
a. Mark it in-progress
b. LAUNCH a subagent with an extremely detailed prompt
c. LAUNCH a validation subagent to verify the work
d. If validation fails → re-launch the work subagent with failure context
e. If validation passes → mark task completed
4. After all tasks complete, LAUNCH a final integration-validation subagent
5. Return results to the user
Task Decomposition
Large tasks MUST be broken into smaller subagent-sized pieces. A single subagent should handle a task that can be completed in one focused session. Rules of thumb:
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.
- 4d ago First seen · 225 lines · 27 tokens per session scan A e4c4f28a234f
RUG is an agent published in the GitHub repository github/awesome-copilot (38,691 stars, last pushed today), licensed MIT. It adds 27 tokens to every session and 2,389 once invoked, about $0.0001 per session on Opus 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
apm-expert
Expert on APM (Agent Package Manager). Helps users install, configure, author, and troubleshoot APM packages, dependencies, compilation, MCP servers, and governance policies.
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-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…
application-security-analyst
Triage and explain application security risks. Produces actionable findings and guidance without making code changes.