floe-guard: Instructions file for Codex

AGENTS.md

floe-guard AGENTS.md is an instructions file for Codex, OpenCode from Floe-Labs/floe-guard. It costs 1,175 tokens per session, scanned A, original, MIT.

A software component that measures the cost of each AI-agent call, including speech recognition, speech synthesis, language-model, and phone costs, and keeps a spending record.

In plain words
What is it for?
Adding cost checks and records to Python or TypeScript agents, including voice agents and agents built with Pipecat, LiveKit, OpenAI, Anthropic, CrewAI, or LangChain.
Why use it?
It helps developers see actual per-call spending and stop an agent before a runaway loop exceeds a chosen dollar limit.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: positional $N argument; mentions Claude Code; mentions AGENTS.md.

This is Floe-Labs/floe-guard's own configuration. It tells Codex and OpenCode how to work on floe-guard 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 floe-guard configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Floe-Labs/floe-guard. 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/Floe-Labs/floe-guard/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/Floe-Labs/floe-guard

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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Per session 1,175 This file is loaded in full into every session.
When invoked 1,175 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.01175 $0.01175
Opus 5.5 $0.00470 $0.00470
Sonnet 5.5 $0.00235 $0.00235
Haiku 4.5 $0.00118 $0.00118

Measured 1mo ago against content hash 5765405069c0, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

floe-guard 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 1mo 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.

AGENTS.md · 83 lines

How it starts

The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — floe-guard

Instructions for AI coding agents. Most often you're here to add floe-guard to an agent (below); the last section covers working on this repo.

What floe-guard is

It tells you what every AI call really costs. It meters STT + TTS + LLM + telephony per call, out of the box (Pipecat and LiveKit, Python & TypeScript), and keeps a live ledger of your agent's real spend. Connect free (one key) for your Coverage Score and 7-day history. It also hard-stops the next turn before it crosses your USD ceiling — a runaway loop dies at $0.10 instead of $4,000. Runs in your process: no account, no signup, no network, no telemetry. It also guards any LLM agent (OpenAI, Anthropic, CrewAI, LangChain, …) via plain check() / record() or an adapter. Python (pip) + TypeScript (npm). MIT. Built by Floe — know what every AI call really costs: cost per call across every vendor, margin per client, and rebilling your own customers off the actuals.

Add it to an agent — unattended steps

  1. Install

    • Python: pip install floe-guard
    • TypeScript / Node: npm i floe-guard
  2. Wire the hard-stop around each model call (check before, record after):

    from floe_guard import BudgetGuard
    
    guard = BudgetGuard(limit_usd=5.00)   # the ceiling
    guard.check()                         # before each LLM call — raises BudgetExceeded if it'd cross
    resp = call_your_llm(...)             # your existing call
    guard.record("gpt-4o", resp.usage.prompt_tokens, resp.usage.completion_tokens)
    

    TypeScript is the same shape (guard.check() / guard.record(...)); see js/.

    • Framework adapters (no manual check/record): OpenAI, Anthropic, Gemini, CrewAI, LangChain, LangGraph, LiteLLM, Vercel AI SDK — README §"Framework adapters".
    • Voice (per-turn): Python floe_guard.integrations.pipecat / .livekit; TS floe-guard/adapters/{livekit,vapi,retell} — reserve-before-turn.
    • Paid tools: reserve_tool() / settle_tool() block before the tool runs.
  3. Verify offline (no key, no network): floe-guard demo — the guard halts a stubbed loop after a few iterations. No repo checkout (the wheel does not ship examples/).

Read the full file on GitHub · 83 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. 1mo ago First seen · 83 lines · 1,175 tokens per session scan A 5765405069c0

Subscribe to this mod's changes

floe-guard AGENTS.md is an instructions file published in the GitHub repository Floe-Labs/floe-guard (354 stars, last pushed yesterday), licensed MIT. It adds 1,175 tokens to every session, about $0.0047 per session on Opus 5.5. 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.

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