Omnigent is an open-source orchestration layer for running and coordinating different AI coding agents through one system. It is for developers who want to combine agents, apply policies and sandboxing, and continue sessions across devices. The catalogue add-ons extend its agent workflows.
Borrowing it
Nothing to install: this file belongs to omnigent-ai/omnigent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/omnigent-ai/omnigent/main/AGENTS.mdgit clone --depth 1 https://github.com/omnigent-ai/omnigentWrote 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/instructions/omnigent-ai/omnigent/agents-md)<a href="https://agentmods.dev/instructions/omnigent-ai/omnigent/agents-md"><img src="https://agentmods.dev/badge/instructions/omnigent-ai/omnigent/agents-md/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/instructions/omnigent-ai/omnigent/agents-md"><img src="https://agentmods.dev/badge/instructions/omnigent-ai/omnigent/agents-md.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 | $0.01827 | $0.01827 |
| Opus 5.5 | $0.00731 | $0.00731 |
| Sonnet 5.5 | $0.00365 | $0.00365 |
| Haiku 4.5 | $0.00183 | $0.00183 |
Grade B, and why
omnigent AGENTS.md scanned grade B with 1 finding 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 2d 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.
Asks the agent to reveal its instructionsmediumSystem prompt leakage
Directions to print, repeat or translate the system prompt extract configuration the operator did not intend to expose.
When you finish a task, print instructions to the user on how to test it: the 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.
Agent guidance
Guidance for AI agents (Claude Code, Copilot, Cursor, etc.) working in this
repository. See CONTRIBUTING.md for the full contributor workflow.
Reuse and design
- Search for and reuse existing helpers before adding code. Refactor an existing implementation if that avoids duplication.
- Use descriptive names; avoid unexplained abbreviations and single-letter names.
Test changes
Before adding test setup, read the test guide and
primitive catalog, then inspect the nearest scenario.
Reuse sufficient coverage unchanged or extend a compatible scenario. Keep input
matrices at the lowest reliable layer; retain E2E for distinct process, transport
or browser boundaries. Reuse primitives with explicit caller inputs and keep
faults and assertions in the test. Explain new setup or a separate E2E in the
PR's Test Plan (Repro uses evidence; Resolve uses test_audit). Count helper changes in
test LOC; fewer lines alone do not establish adequate coverage.
- Add a unit test for non-trivial functions, methods, and exported APIs. Add coverage when changed behavior needs it.
- Run the relevant tests before submitting. Document unrelated pre-existing failures in the PR description.
Dependency changes
When raising a dependency floor or adding a dependency, keep it installable from
package mirrors that embargo new releases (see the dependency notes in
CONTRIBUTING.md) and run just check-internal-mirror when you can reach the
Databricks PyPI proxy. If a mirror lacks the version you need, keep the floor
below it and pin the newer release only in uv.lock; do not work around the
mirror with a local or temporary index. Never add the dependency-floor-approved
label yourself; a human maintainer adds it after checking the mirror.
Committing
The pre-commit hooks are the local gate, and CI runs the same checks. They
run on git commit and again on git push only after they are installed:
just ensure does that (or just hooks on its own), once per clone. Worktrees
share the clone's .git, so one install covers them all.
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.
- 2d ago Changed · +10 lines · +181 tokens per session a9a4e479f1ed
- 4d ago Changed · +10 lines · +125 tokens per session e82935c18d41
- 13d ago Changed · +11 lines · +91 tokens per session 263d278855a4
- 15d ago Changed · +11 lines · +140 tokens per session a26cb659ab1e
- 27d ago Changed · +11 lines · +165 tokens per session 6348dec0dfd4
- 28d ago Changed · +3 lines · +39 tokens per session 9d92c14e753f
- 1mo ago Changed · +12 lines · +107 tokens per session ebcae40aacd0
- 2mo ago First seen · 94 lines · 979 tokens per session scan B 629f4b8a5685
omnigent AGENTS.md is an instructions file published in the GitHub repository omnigent-ai/omnigent (11,100 stars, last pushed today), licensed Apache-2.0. It adds 1,827 tokens to every session, about $0.0073 per session on Opus 5.5. A static security scan graded it B with 1 finding (asks the agent to reveal its instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.