codex-token-meter AGENTS.md

A development guide for Codex Token Meter, a native macOS menu-bar app written in Swift that tracks AI token usage and related service information.

In plain words
What is it for?
Use it when changing token, quota, cost, parser, or interface behavior, and when running the project's build and verification checks.
Why use it?
It identifies the important source files and gives exact commands for compiling the app and checking its parser, live quota, service status, and dashboard output.

Instructions file for CodexOpenCode

Install

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.

agentmods
npx agentmods add instructions/prefect12/codex-token-meter/agents-md
Clone the repo
git clone --depth 1 https://github.com/prefect12/codex-token-meter

Made for: Codex, OpenCode.

Per session 1,357 This file is loaded in full into every session.
When invoked 1,357 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 $0.01357 $0.01357
Opus 5 $0.00678 $0.00678
Sonnet 5 $0.00271 $0.00271
Haiku 4.5 $0.00136 $0.00136

Measured 2d ago against content hash d77e8555cbe1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

codex-token-meter 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 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.

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 · 76 lines

How it starts

The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Token Meter Development Guide

Project Shape

  • This is a native macOS menu bar app built directly with swiftc.
  • The app entrypoint lives in Sources/CodexTokenMeter/main.swift; supporting code is split into focused files under the same directory.
  • The companion Task Bar app lives in Sources/CodexPetBar/main.swift and is part of the same product family, not a separate design surface.
  • build.sh compiles every Swift file under Sources/CodexTokenMeter, so future file splits do not need build-script changes.
  • Prefer small, behavior-preserving changes unless you are explicitly doing a planned refactor.
  • Read docs/ARCHITECTURE.md before changing parser, quota, cost, or UI behavior.

Build And Verification

  • Compile check: ./build.sh
  • CLI parser check: "./build/AI Token Meter.app/Contents/MacOS/CodexTokenMeter" --print --window=week --quota=all
  • Live quota check: "./build/AI Token Meter.app/Contents/MacOS/CodexTokenMeter" --print-live
  • Service-status check: "./build/AI Token Meter.app/Contents/MacOS/CodexTokenMeter" --print-service-status
  • Dashboard render check for UI changes: "./build/AI Token Meter.app/Contents/MacOS/CodexTokenMeter" --render-dashboard=/tmp/ai-token-meter-dashboard.png

--print-live, --print-profile, --print-service-status, and dashboard rendering can depend on Codex login state or network availability. Do not treat their unavailability as a compile regression unless the failure is caused by local code.

Git Workflow

  • Prefer merging changes through pull requests. Do not merge directly into main unless the user explicitly asks for it.
  • All source, behavior, or UI changes must use this sequence: a focused branch → PR → merged main → fetch origin/main → build and install from that exact merged revision. Do not install an unmerged working-tree build as the delivered app.
  • Before calling a change complete, verify the PR merge, confirm local HEAD equals origin/main, then run the relevant checks and validate the installed /Applications/AI Token Meter.app surface.

Read the full file on GitHub · 76 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. 2d ago First seen · 76 lines · 1,357 tokens per session scan A d77e8555cbe1

Subscribe to this mod's changes

codex-token-meter AGENTS.md is an instructions file published in the GitHub repository prefect12/codex-token-meter (5 stars, last pushed 2d ago), licensed MIT. It adds 1,357 tokens to every session, about $0.0068 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.