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.
npx agentmods add instructions/nvidia/model-optimizer/agents-mdgit clone --depth 1 https://github.com/NVIDIA/Model-OptimizerWhat 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 | $0.00920 | $0.00920 |
| Opus 5 | $0.00460 | $0.00460 |
| Sonnet 5 | $0.00184 | $0.00184 |
| Haiku 4.5 | $0.00092 | $0.00092 |
Grade A, and why
Model-Optimizer AGENTS.md 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 yesterday.
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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Instructions for ModelOpt
These instructions apply to AI-assisted work in this repository.
Repository orientation
- Start with
README.mdfor project overview and install. - Use
modelopt/for source,tests/for focused test coverage, andexamples/ordocs/for usage patterns. - Agent skills live under
plugins/modelopt/skills/, the installable plugin's canonical skill tree..agents/skillsand.claude/skillsexpose those skills through relative symlinks. Shared agent config and scripts remain under.agents/. See.agents/README.mdfor the convention.
Coding guidelines
- Coding guide: Code development and review require reading and following the coding standards in CONTRIBUTING.md; do not skip this step.
- Use relative paths from the repo root in commands and file references.
Iterative development
- Running tests: Follow the
writing and running tests
instructions. For fast initial iteration, choose focused tests for the
changed area from
tests/. - Running pre-commit: Follow the pre-commit hook instructions. Hooks may modify files; review and re-stage those changes before committing.
- Signed commit: Use
git commit -s -S -m "<message>"for commits so they follow the signing your work requirements. - Never
git pushwithout explicit approval in the current turn. Commit locally is fine; publishing to a remote is not. - After
git commit, stop and wait for the user to say "push", "publish", "ship", or equivalent before runninggit push,gh pr create, or any push-option flags like-o merge_request.create.
Contributing and PR readiness
- Before opening or marking a PR ready for review, read the submitting your code guidance.
- Read
.github/PULL_REQUEST_TEMPLATE.mdand satisfy the checklist. - PR description: fill the template sections — what changed and why, a usage snippet if it adds an API or flag, and what you actually ran under Testing. Root cause, benchmark numbers, and design rationale belong here. Don't restate the diff file by file.
- Only changelog-worthy changes get a
CHANGELOG.rstentry: new features, backward breaking changes, deprecations, and fixes for critical or known bugs from a previous release. Skip bugs introduced and fixed within the same unreleased cycle. - Keep each entry to one or two sentences written for external users: what
changed and what they need to do. No internal bug numbers (e.g. NVBug IDs),
root-cause analysis, or implementation detail — that belongs in the PR
description. File features under the matching
**New Features**sub-section used by recent releases (e.g.*Quantization*,*Speculative Decoding*,*Megatron Framework (M-LM / M-Bridge)*,*Misc*) rather than relabeling existing ones.
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.
- yesterday First seen · 74 lines · 920 tokens per session scan A f791a2eb9d3d
Model-Optimizer AGENTS.md is an instructions file published in the GitHub repository NVIDIA/Model-Optimizer (3,612 stars, last pushed yesterday), licensed Apache-2.0. It adds 920 tokens to every session, about $0.0046 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 2026-08-30.
Other instructions, from other repositories
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
buildNext
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
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, applying the notice (cutover) and fallback chain (never fail the build).
spec-kit AGENTS.md
Instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
langchain 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.