Borrowing it
Nothing to install: this file belongs to click6067-ship-it/fitllm-engine. 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/click6067-ship-it/fitllm-engine/master/AGENTS.mdgit clone --depth 1 https://github.com/click6067-ship-it/fitllm-engineWrote 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/click6067-ship-it/fitllm-engine/agents-md)<a href="https://agentmods.dev/instructions/click6067-ship-it/fitllm-engine/agents-md"><img src="https://agentmods.dev/badge/instructions/click6067-ship-it/fitllm-engine/agents-md.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 | $0.00749 | $0.00749 |
| Opus 5 | $0.00375 | $0.00375 |
| Sonnet 5 | $0.00150 | $0.00150 |
| Haiku 4.5 | $0.00075 | $0.00075 |
Grade A, and why
fitllm-engine 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 today.
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 — 36 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — how AI agents should use this repo
Purpose: fitllm-engine answers "will this LLM fit this hardware?" with auditable, architecture-aware memory estimates (MLA / sliding-window / hybrid-linear / MoE), while keeping runtime and OS reserves explicit.
Use it without cloning
- One-shot answer:
GET https://fitllm.run/api/check?model=<name>&gpu=<name|a%2Bb>or&ram=<GB>— no auth, fuzzy names, JSON (or&format=text|md). Won't-fit responses include a computedfix. - MCP:
https://fitllm.run/api/mcp— toolscheck_llm_fit/what_fits_on_hardware/list_supported; resourcesfitllm://models|hardware|census|engine. Read-only, idempotent. - CLI guard:
npx fitllm "<model>" --gpu "<gpu>"→ exit 0/1. Use it to gate model downloads in scripts/CI. - Precomputed data (CC0):
census/census-v1.{csv,json}— 9,477 verdicts, model × device × quant. Also on HF Datasets. - Agent answer recipe: https://fitllm.run/agent/answer-with-citation.md
Use it as a library
Single ESM file, zero deps: engine.js (also https://cdn.jsdelivr.net/npm/fitllm-engine@latest/engine.js).
import { simulate, LOCAL_MODELS, parseHfConfig, GPUS, gpuDevice, combineGpus, simulateStack } from './engine.js';
simulate(model, 64, 131072, 8) // Mac 64GB, 128K ctx, 8-bit → {verdict, used, free, ...}
simulate(model, gpuDevice(gpu), ctx, {weightBpw, kvBits}) // GPU path; combineGpus([a,b]) for rigs
parseHfConfig(id, configJson, totalSizeBytes) // modeled HF architecture → engine shape; unsupported configs fail closed
Rules for agents modifying this repo
- Every hardware number needs ≥2 independent source URLs embedded next to the value — no source, no merge.
- Engine math changes require conformance vectors to pass:
node vectors/run.mjs(30 byte-exact anchors). A port in any language is conformant iff all vectors pass. - Run
npm test(CLI behavior) — exit codes 0/1/2 are a public contract. npm run censusregenerates the dataset after model/hardware changes.- Never add tokens/sec predictions — fit is a verifiable claim, speed is not (project principle).
- This repo mirrors
fitllm-v2/src/lib/engine.js(private) — upstream changes land there first.
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.
- today Changed e267ea292c53
- yesterday Changed 88a17cf7d5a7
- 2d ago Changed · +1 lines · +23 tokens per session 684f37280289
- 6d ago First seen · 35 lines · 726 tokens per session scan A f1eef1cbc7ad
fitllm-engine AGENTS.md is an instructions file published in the GitHub repository click6067-ship-it/fitllm-engine (8 stars, last pushed today), licensed MIT. It adds 749 tokens to every session, about $0.0037 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 2026-08-31.
Other instructions, from other repositories
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.
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.
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).
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).
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.
spec-kit AGENTS.md
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.