Count AI coding-agent tokens per git branch and report them on GitHub PRs
Project description
tokenchecker
Count AI coding-agent tokens per git branch — across sessions and machines — and post the totals as a comment on the GitHub PR when it opens.
Supported agents (parsed from their local logs, no API keys needed):
| Tool | Data source | Branch attribution |
|---|---|---|
| Claude Code | ~/.claude/projects/<project>/*.jsonl (per-message usage) |
exact — gitBranch recorded per message |
| Codex CLI | ~/.codex/sessions/Y/M/D/*.jsonl (token_count events) |
branch recorded in session metadata |
| Gemini CLI | ~/.gemini/tmp/<sha256(cwd)>/chats/*.json (per-message tokens) |
inferred from your repo's HEAD reflog at message time |
| Cursor | state.vscdb (per-message tokenCount in bubble records) |
inferred from HEAD reflog at message time |
Single-file, stdlib-only Python 3.9+. macOS and Linux (Cursor paths auto-detected on macOS; override with env vars elsewhere).
How it works
your laptop origin (GitHub) PR
┌─────────────────────┐ ┌──────────────────────┐
│ claude / codex / │ git push │ refs/token-usage/ │ GitHub Action:
│ gemini / cursor logs│ ──────────► │ laptop-a1b2c3d4 │ fetch refs/token-usage/*
│ │ │ (pre-push │ desktop-e5f6a7b8 │ aggregate head branch
│ ▼ │ hook runs │ coworker-c9d0e1f2 │ upsert PR comment
│ tokenchecker sync │ `sync`) └──────────────────────┘
└─────────────────────┘
tokenchecker collectscans the local logs of all four tools, keeps only records whose working directory (or remote URL) matches the current repo, normalizes them into deduplicatable records (input / cache_read / cache_write / output / total+ branch + timestamp + machine), and stores them under.git/tokenchecker/.tokenchecker pushpublishes the machine's records to a custom git refrefs/token-usage/<machine-id>on origin. Each machine owns exactly one ref, so there are never conflicts, and no external storage is needed. Records are idempotent — re-collecting and re-pushing never double-counts.- A
pre-pushgit hook runssync(= collect + push) automatically, so usage data reaches origin together with the branch you're about to open a PR for. If the branch has an open PR and theghCLI is available, the hook also upserts the sticky PR comment right then — no CI or repo files required. - Optionally, a tiny committed workflow re-renders the comment on every
pull_requestevent via theZohaibAhmed/tokenchecker@v0action, so the comment stays current no matter who pushes or whether they havegh.
Setup
Global (recommended): once per machine
pipx install tokenchecker # or: uv tool install tokenchecker
# or, straight from git (works for private forks too):
# pipx install git+https://github.com/ZohaibAhmed/tokenchecker
# or, no package manager at all — the script is a single stdlib-only file:
# python3 tokenchecker.py install --global (from a checkout)
tokenchecker install --global
This copies the script to ~/.tokenchecker/, adds a tokenchecker CLI wrapper at
~/.tokenchecker/bin/, and sets git's global core.hooksPath to a directory of
dispatcher hooks that chain to each repository's own .git/hooks/* first, then record
token usage on pre-push. Every repo on the machine is covered automatically — no
per-repo, per-clone setup.
- Opt a repo out:
git config tokenchecker.enabled false - Repos that set
core.hooksPaththemselves (e.g. husky) bypass the global hooks — add the sync line to their hook system or use the per-repo install there. - If you already had a global
core.hooksPath, the installer refuses to clobber it and prints the one line to add to your existing pre-push hook. - Hook runs are quiet when there is nothing new; you only see output when records are actually collected or pushed.
PR comments need nothing more. When you git push a branch with an open PR, the
hook posts/updates the report comment straight from your machine using the gh CLI
(opt out with git config tokenchecker.comment false). For teams that want the comment
maintained by CI as well — so it updates regardless of who pushes — commit one small
workflow per repo: run tokenchecker install there and commit
.github/workflows/token-usage.yml (a dozen boilerplate lines that call the
ZohaibAhmed/tokenchecker@v0 action; the action pip-installs tokenchecker in CI, so
there is nothing else to vendor or keep up to date).
Per repository (alternative)
# one time, by anyone: add the CI workflow
tokenchecker install # run from inside the target repo
git add .github/workflows/token-usage.yml
git commit -m "add tokenchecker workflow"
# every contributor, once per machine:
tokenchecker install --global # (or `tokenchecker install` per clone)
install is idempotent. It:
- writes
.github/workflows/token-usage.yml(committed) — a few boilerplate lines calling theZohaibAhmed/tokenchecker@v0action, which installs tokenchecker from PyPI in CI (pin withwith: {version: "tokenchecker==0.3.0"}if you like) - appends a guarded block to
.git/hooks/pre-push(local; preserves existing hooks; skipped when the global install already covers the repo) - with
--vendor, embeds the script atscripts/tokenchecker.pyand writes a fully self-contained workflow instead — for repos that can't use PyPI or third-party actions in CI - with
--claude-hook, also adds a Claude CodeSessionEndhook to.claude/settings.jsonso usage syncs when a Claude session ends, not just on push
Commands
tokenchecker sync # collect + publish (what the hook runs)
tokenchecker collect --dry-run # preview per-branch usage, write nothing
tokenchecker status # when did it last run, what's synced where
tokenchecker report # all branches, all machines, with costs
tokenchecker report --branch feature/x --markdown # PR-comment format
tokenchecker report --json # raw records
tokenchecker comment # post/update the PR comment for this branch (gh)
Seeing it run
- On every
git pushthe hook prints two lines in your terminal:tokenchecker: collected 7 records (claude-code=4, codex=1, gemini=1, cursor=1); 0 new; store has 6 tokenchecker: pushed 6 records to origin refs/token-usage/laptop-a1b2c3d4 statusshows the machine id, the local store, a timestamped log of recent collect/push runs (kept in.git/tokenchecker/log), every synced machine ref with its last-push time, and which refs exist on origin.- In CI, the Action run appears in the PR's Checks tab; the rendered report is printed in the job log and on the run's Summary page, in addition to the PR comment itself.
Useful flags: --since N (lookback days, default 90), --remote NAME (default origin),
--repo PATH (default: cwd).
The PR comment
## 🤖 AI token usage for `feature/x`
| Tool | Model | Sessions | Msgs | Input | Cache read | Cache write | Output | Total | Est. cost |
| claude-code | claude-fable-5 | 2 | 3 | 211 | 2,000 | 100 | 74 | 2,385 | $0.01 |
| codex | gpt-5.5 | 1 | 1 | 500 | 400 | 0 | 100 | 1,000 | $0.01 |
| ...
Cache reads are reported separately from fresh input tokens (they're billed differently and dominate agent usage), and the per-machine breakdown is in a collapsible section.
Cost estimates
Every report includes an Est. cost column: the four token buckets priced at each model's API list rates (input / cache read / cache write / output). It's an estimate — subscription plans (Claude Max, ChatGPT plans, Cursor Pro) bill differently — but it answers "what did this branch consume in model time".
Costs are computed at report time, never stored, so a price update retroactively corrects every report. Prices resolve through three layers, and each report's footer says which one was used (and its date):
TOKENCHECKER_PRICES=<file>— pin your own rates. Accepts either LiteLLM's schema or a simple{ "<model>": {"input": $, "cache_read": $, "cache_write": $, "output": $} }map in $/MTok.- Live fetch of LiteLLM's community price table,
cached for 7 days at
~/.tokenchecker/prices.json(skip withTOKENCHECKER_NO_NETWORK=1). CI always gets fresh prices this way. - Embedded fallback table baked into the script, regenerated monthly by the
update-pricesworkflow (which opens a PR only when prices drifted).
Models with no known pricing show —, are excluded from the total, and are listed in
a footnote — never silently counted as $0 without a trace.
Semantics & accuracy notes
- Dedup: every record has a stable id (message id / session id / bubble id). Streaming snapshots, re-collection, and multi-machine overlap all collapse to the max-total record, so numbers never double-count.
- Codex reports a cumulative counter per session; tokenchecker takes the session's final counter (one record per session), attributed to the branch the session started on.
- Gemini / Cursor don't record the branch, so tokenchecker replays your repo's
HEADreflog to determine which branch was checked out at each message's timestamp. This is accurate unless you rewrite history, and reflog entries expire after ~90 days (git's default) — matching the default--since 90window. - Cursor exposes
inputTokens/outputTokensper message locally but no cache split. Older Cursor conversations (before it started persistingtokenCount) report 0. - Tokens spent on a machine only reach the PR after that machine pushes (any push — the
hook publishes usage for all branches, not just the pushed one) or runs
syncmanually. - Forks: contributors pushing from forks publish
refs/token-usage/*to their fork, which the base repo's Action can't see. Same-repo branches are fully supported.
Env overrides
TOKENCHECKER_MACHINE_ID, TOKENCHECKER_CLAUDE_DIR, TOKENCHECKER_CODEX_DIR,
TOKENCHECKER_GEMINI_DIR, TOKENCHECKER_CURSOR_GLOBAL_DB, TOKENCHECKER_CURSOR_WS_DIR,
TOKENCHECKER_PRICES (path to a pinned price table), TOKENCHECKER_NO_NETWORK
(never fetch live prices).
Setting TOKENCHECKER_SKIP=1 disables the pre-push hook (used internally to prevent
recursion).
Cleaning up
Usage refs are plain git refs; delete them with
git push origin --delete refs/token-usage/<machine-id> and remove
.git/tokenchecker/ locally. Nothing else is stored anywhere.
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The following attestation bundles were made for tokenchecker-0.3.0-py3-none-any.whl:
Publisher:
release.yml on ZohaibAhmed/tokenchecker
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Statement type:
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