codex-usage-tracking 0.3.2

Unofficial local Codex plugin and dashboard for investigating aggregate token usage, costs, caching, and thread patterns.

Codex Usage Tracker

Local-first dashboard, Codex plugin, and companion skill for understanding where your Codex tokens and usage credits are going.

Unofficial project: Codex Usage Tracker is an independent open-source project. It is not made by, affiliated with, endorsed by, sponsored by, or supported by OpenAI. OpenAI and Codex are trademarks of OpenAI; this project only reads local log files from your machine.

Codex Usage Tracker reads the JSONL logs already written by Codex, indexes aggregate usage counters into SQLite, and gives you a dashboard, CLI, and MCP tools for investigating real usage patterns. It keeps prompts, assistant messages, tool output, pasted secrets, and raw transcript content out of SQLite, CSV exports, and generated dashboard HTML.

Built for developers using Codex locally who want to know which threads, models, subagents, and long chats are driving usage without uploading logs anywhere. The public PyPI package is codex-usage-tracking, and it installs the codex-usage-tracker command.

After install, you get a localhost dashboard, a local SQLite aggregate index, CLI reports, MCP tools, and a companion Codex skill for asking questions like "what drove my usage this week?"

Quick Install

python -m pip install --user pipx
python -m pipx ensurepath
pipx install codex-usage-tracking
codex-usage-tracker setup
codex-usage-tracker serve-dashboard --open

Use your normal Python launcher for your platform: python3 is common on macOS/Linux, and py may be preferable on Windows. On macOS with Homebrew, brew install pipx is also fine.

serve-dashboard refreshes active-session usage before opening by default. Use --no-refresh only when you intentionally want to inspect the cached local index.

Package naming: the PyPI distribution is codex-usage-tracking; the installed command is codex-usage-tracker; the GitHub repository remains douglasmonsky/codex-usage-tracker. The codex-usage-tracker PyPI name is not this project, so avoid similarly named packages when following these docs.

Source install for development or branch testing:

pipx install "git+https://github.com/douglasmonsky/codex-usage-tracker.git"

setup installs or refreshes the local Codex plugin wrapper, initializes local config templates when needed, refreshes the aggregate index, runs codex-usage-tracker doctor, and tells you whether Codex needs a restart for plugin discovery.

Want Codex to do it for you? Paste: Install codex-usage-tracking with pipx, run codex-usage-tracker setup, and open the Codex Usage Tracker dashboard.

After plugin discovery, Codex can use the companion usage skill to refresh local aggregates, call the MCP tools, and explain usage patterns conversationally. Examples: MCP And Codex Skills.

If you only want plugin registration after installing the package:

codex-usage-tracker install-plugin

More install paths: Install Guide.

Platform Support

The core app is not macOS-only. The CLI, SQLite index, dashboard generator, and localhost server are Python-based and CI-tested on Ubuntu for Python 3.10-3.13. It defaults to ~/.codex for local Codex logs and ~/.codex-usage-tracker for tracker data; pass --codex-home or --db when your local layout differs. Codex plugin discovery depends on Codex's local plugin directories on your machine, so run codex-usage-tracker doctor after setup if plugin registration does not appear in Codex.

Dashboard Preview

The Calls table is the main investigation surface: filter, sort, inspect details, and export the exact aggregate rows you are looking at.

Threads view groups related calls so long chats, subagents, and auto-review passes are easier to reason about as one work session.

The details panel keeps the primary cost, cache, context, allowance, and pricing signals visible before raw identifiers.

Insights still gives a fast triage layer for costly threads, low cache reuse, context bloat, and pricing gaps.

The dashboard screenshots use synthetic aggregate fixture data, and the companion prompt and chat previews are synthetic. They do not contain prompts from local logs, assistant responses, tool output, real thread names, real usage totals, or real Codex session content. See the Dashboard Guide for the full walkthrough.

If this helped you track Codex usage, starring the repo helps others find it. Issues and feature requests are welcome.

Why This Exists

Codex can quietly burn usage through long-running chats, low cache reuse, reasoning spikes, spawned subagents, and auto-review passes. This tool turns the aggregate counters already on your machine into an insight-first dashboard and scriptable local APIs.

Use it to answer:

• Which threads used the most tokens, estimated cost, or Codex credits?
• Are long chats bloating because of accumulated context?
• Which model or reasoning effort is driving usage?
• Are subagents or auto-review passes adding unexpected cost?
• Which calls have low cache reuse, high context pressure, reasoning spikes, or pricing gaps?
• Which projects, project tags, or active directories are consuming the most usage?
• What should Codex inspect next using the companion usage skill?

Long Chats Can Bloat Fast

Prompt caching helps, but cached input is not the same as no input. Long threads can accumulate a large cached context, and each new turn may still include cached input plus fresh uncached input, output tokens, reasoning output, and tool-related context.

The dashboard makes that pattern visible with:

• Cached input
• Uncached input
• Session cumulative
• Context use
• Cache ratio

Practical takeaway: when old context is no longer useful, starting a fresh thread can be more efficient than dragging a large cached history forward. That is not a rule for every task, but it is one of the clearest usage patterns the tracker is designed to reveal.

First Useful Workflow

codex-usage-tracker update-pricing
codex-usage-tracker update-rate-card
codex-usage-tracker setup
codex-usage-tracker serve-dashboard --open

Then:

1. Leave Live enabled while working, or click Refresh after a Codex run finishes.
2. Start in Insights and scan the Needs Attention cards.
3. Use Time presets or calendar fields to focus on today, this week, the last 7 days, this month, or a custom range.
4. Use investigation presets for highest-cost threads, highest-credit calls, context bloat, cache misses, pricing gaps, or estimated-price review.
5. Open Threads to see how a conversation grew and whether subagent or auto-review work attached to it.
6. Hover or click rows to inspect aggregate fields in Call Details.
7. Use Load context only when aggregate fields are not enough; context is fetched on demand from the local source JSONL and is not saved into SQLite or the dashboard.

Optional allowance context:

codex-usage-tracker parse-allowance "5h 79% 6:50 PM Weekly 33% Jun 7"

The tracker cannot read your logged-in ChatGPT plan or live remaining usage automatically. Allowance values are only as accurate as the values you manually copy from Codex Settings, /status, or another trusted usage display. Details: Pricing, Credits, And Allowance.

What It Includes

• Local SQLite index at ~/.codex-usage-tracker/usage.sqlite3.
• Static dashboard generation plus localhost live refresh.
• Insights, Calls, and Threads dashboard views.
• Active-only dashboards by default, with an explicit All history toggle for archived sessions.
• CLI summaries, queries, CSV export, dashboard generation, doctor checks, and support bundles.
• MCP tools for Codex sessions that want to query local usage data.
• Companion Codex skills for operational setup and conversational usage analysis.
• Optional local pricing, Codex credit, allowance, threshold, project alias, and privacy-mode configuration.

Common Commands

codex-usage-tracker summary --preset last-7-days
codex-usage-tracker query --since 2026-06-01 --min-credits 1
codex-usage-tracker session <session-id>
codex-usage-tracker export --output usage.csv
codex-usage-tracker open-dashboard
codex-usage-tracker support-bundle --output ~/.codex-usage-tracker/support-bundle.json

Full command reference: CLI Reference.

Data Privacy

The tracker stores aggregate metrics only: session ids, timestamps, local source paths, thread labels, cwd/project metadata, model labels, reasoning effort, token counters, pricing/credit annotations, and derived ratios.

It does not store prompts, assistant messages, tool output, pasted secrets, raw transcript snippets, or raw context in SQLite, CSV exports, generated dashboard HTML, or synthetic screenshots.

On-demand context loading reads a single original local JSONL file only after an explicit row action, redacts common secret patterns, caps returned text size, and can start off until you enable it from the details panel:

codex-usage-tracker serve-dashboard --no-context-api --open

For shared artifacts, use:

codex-usage-tracker --privacy-mode redacted dashboard --open
codex-usage-tracker --privacy-mode strict export --output usage-redacted.csv

Full model: Privacy Guide.

Documentation

• Install Guide
• Dashboard Guide
• CLI Reference
• Pricing, Credits, And Allowance
• MCP And Codex Skills
• Privacy Guide
• Architecture
• CLI And MCP JSON Schemas
• Development And Release

Codex-Assisted Install

Open a Codex session on your machine and paste this:

Install and configure Codex Usage Tracker.
Install the PyPI distribution codex-usage-tracking with pipx. The installed command should be codex-usage-tracker. Use pipx install "git+https://github.com/douglasmonsky/codex-usage-tracker.git" only for branch testing or if PyPI is temporarily unavailable.
If pipx is missing, install it with the platform's Python launcher or use a local virtual environment.
After installation, run codex-usage-tracker setup and serve-dashboard --open.
Verify the dashboard opens locally and tell me the dashboard URL plus whether I need to restart Codex for plugin discovery.

This is optional. The normal shell install above is the fastest trusted path for most users.

Current Limitations

• This is a sidecar dashboard and plugin, not a native Codex chat overlay.
• Token counts come from Codex's logged counters; the tracker does not re-tokenize prompts.
• Pricing and Codex credit estimates depend on local rate data and confidence labels.
• Remaining 5-hour and weekly allowance is not read automatically from the logged-in account.
• Local Codex logs may not include usage from other ChatGPT agentic surfaces that share the same allowance.
• Parent-child thread relationships are only as good as the metadata Codex logs; inferred auto-review attachments are labeled as inferred.

Roadmap

• Improve the Set limits flow with a paste/import experience for 5-hour and weekly allowance snapshots.
• Track allowance snapshot history so local Codex credits can be compared against visible remaining-usage changes over time.
• Clarify top-card token accounting by showing output tokens and reasoning output as a subset instead of implying all token cards add together.
• Add more insight presets for cache drift, context growth, subagent-heavy workflows, and pricing/credit confidence gaps.
• Keep the allowance provider boundary ready for an official usage or allowance API if one becomes available.
• Continue reducing setup friction for pipx installs, local plugin discovery, and Codex companion skill usage.

Development

git clone https://github.com/douglasmonsky/codex-usage-tracker.git
cd codex-usage-tracker
python3 -m venv .venv
. .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install ".[dev]"
python -m pytest

Run the full local CI gate before pushing to main. See Development And Release.