fitllm-engine: Instructions file for Codex

AGENTS.md

fitllm-engine AGENTS.md is an instructions file for Codex, OpenCode from click6067-ship-it/fitllm-engine. It costs 749 tokens per session, scanned A, original, MIT.

Project instructions for fitllm-engine, a tool that checks whether a particular language model fits a device's memory. A language model is the software behind many AI systems, while quantization stores it in a smaller format.

In plain words
What is it for?
Checking models against GPUs or RAM, blocking downloads in scripts or CI, finding models that fit available hardware, and using the engine's precomputed compatibility data.
Why use it?
They let an agent check hardware fit through an API, MCP, command line, or JavaScript library instead of cloning the project, and explain the project's exact memory calculations.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions AGENTS.md.

This is click6067-ship-it/fitllm-engine's own configuration. It tells Codex and OpenCode how to work on fitllm-engine itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything fitllm-engine configures →

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/click6067-ship-it/fitllm-engine/master/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/click6067-ship-it/fitllm-engine

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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README.md
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Per session 749 This file is loaded in full into every session.
When invoked 749 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured today against content hash e267ea292c53, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

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.

AGENTS.md · 36 lines

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 computed fix.
  • MCP: https://fitllm.run/api/mcp — tools check_llm_fit / what_fits_on_hardware / list_supported; resources fitllm://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

  1. Every hardware number needs ≥2 independent source URLs embedded next to the value — no source, no merge.
  2. 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.
  3. Run npm test (CLI behavior) — exit codes 0/1/2 are a public contract.
  4. npm run census regenerates the dataset after model/hardware changes.
  5. Never add tokens/sec predictions — fit is a verifiable claim, speed is not (project principle).
  6. This repo mirrors fitllm-v2/src/lib/engine.js (private) — upstream changes land there first.

Read the full file on GitHub · 36 lines

Changes

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.

  1. today Changed e267ea292c53
  2. yesterday Changed 88a17cf7d5a7
  3. 2d ago Changed · +1 lines · +23 tokens per session 684f37280289
  4. 6d ago First seen · 35 lines · 726 tokens per session scan A f1eef1cbc7ad

Subscribe to this mod's changes

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.

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