Skip to main content

codex-stats

codex-stats is a local analytics tool for coding agents.

It reads local session data from every coding assistant installed on the machine and surfaces:

  • a browser dashboard with an Overview tab for every tool combined, plus one tab per tool (Codex, OpenCode, Claude Code, Hermes)
  • day, week, month, and all-time windows inside every tab
  • model and project breakdowns
  • recent session history
  • estimated token-based cost (or each tool's own recorded cost when available)
  • per-tool cost overrides and a stacked per-tool token trend on the Overview
  • branch-level spend: a "Branches" panel that ranks work by cost per branch instead of per repository, and flags branches that went quiet — paid-for work that stopped and never finished
  • spend joined to the work it bought: an "Efficiency" panel reporting cost per 1k lines changed, cost per file, cost per editing session, the share of spend that went to sessions which changed nothing, a rework ratio, and the files that were rewritten most across every project at once
  • per-tool efficiency on the Overview, ranking each tool's spend against the lines it actually changed, so "which of my agents is worth it" has an answer
  • a provider breakdown showing which vendor each dollar went to, derived from the model name each session recorded
  • a reasoning-token share in Work Patterns, for models that bill thinking separately
  • anomaly-aware usage insights and recommendations
  • file-level impact tracking: a "Most Edited Files in This Project" table inside each project drilldown, showing per-file edit counts and add/delete line totals parsed from Codex and Claude Code rollouts
  • tool behavior tracking: a "Tool Behavior" panel showing the tools each agent actually called — normalized into shared categories (Read, Edit, Execute, Search, Web, Subagent, Plan), with per-tool failure rates, repeated-call detection, read/write ratio, and abandoned-turn counts, across every tool with recorded calls
  • shareable JPG cards and browser PDF export from the dashboard

Data Sources

Every tool below always gets a tab, whether or not local data exists. Tools with no sessions render an empty state instead of being hidden.

Tool Location Notes
Codex ~/.codex state_5.sqlite + rollout JSONL files, including git branch
OpenCode ~/.local/share/opencode/opencode.db recorded cost + tokens per session
Claude Code ~/.claude/projects/**/*.jsonl per-project transcripts, including git branch
Hermes ~/.hermes/state.db recorded cost + tokens per session

Use these environment variables to point at non-default locations (also used for test isolation):

  • CODEX_HOME (Codex), CODEX_STATS_OPENCODE_HOME (OpenCode), CODEX_STATS_CLAUDE_PROJECTS_DIR (Claude), CODEX_STATS_HERMES_HOME (Hermes)

Reading a session means parsing its rollout or transcript line by line, and that cost is linear in total history on every launch, so each source reads only the 2,000 most recent sessions. This keeps startup predictable on long histories and is invisible on normal ones. When it does drop history, the dashboard says so above the metrics, naming each source it truncated, rather than reporting a partial history as a complete one.

  • CODEX_STATS_MAX_SESSIONS=N reads the N most recent sessions per source. Set it to 0 to read everything and get exact figures, which takes proportionally longer on a long history.

Install

pipx install codex-stats

Or with pip:

python3 -m pip install codex-stats

Command Reference

There is exactly one command, and it takes no options:

codex-stats

It reads local session data, writes a standalone dashboard HTML file to ~/.cache/codex-stats/dashboard.html, and opens it in your default browser. The path is fixed rather than a fresh temporary file, so the dashboard can be bookmarked and reloaded in place; each run overwrites it and the browser is given the file's timestamp so a reload always shows the run you just made, not a cached copy of the last one.

Override the location with XDG_CACHE_HOME.

Inside the dashboard, use the action bar to:

  • switch tools with the Overview / Codex / OpenCode / Claude Code / Hermes tab row
  • switch between Day, Week, Month, and All Time inside the active tool
  • print the active tool and window to PDF
  • download shareable JPG cards for summary, cost, focus, and project share

How It Works

codex-stats does not proxy or intercept API traffic. It reads local artifacts: Codex state_5.sqlite and rollout files, the OpenCode database, Claude Code project transcripts, and the Hermes database, then normalizes everything into one session model.

Notes

  • Branches are grouped per repository. A branch name is only unique inside its own checkout, so feature/login in two projects is tracked as two branches. Codex reads the branch from its session database and Claude Code records one per event; OpenCode records none at all, so its sessions never appear in the Branches panel. Hermes reads a branch from its own database, but leaves it null for sessions started outside a checkout, so its sessions appear only when one was recorded. A detached checkout is reported as having no branch rather than as a branch called HEAD. If a session switched branches mid-run, it is attributed to the branch most of its events landed on.

  • A branch "goes quiet" after 14 days without a session. Those are listed and totalled separately, because a branch that consumed tokens and then stopped is work that was paid for and never finished — invisible in a project-level view, where every branch of a repository collapses into one number.

  • Vendors are resolved from the model name, not the recorded provider. Codex records the real vendor (openai), but OpenCode and Hermes record their own CLI name there instead, and those may route to any vendor, so grouping on that field would answer "which CLI" while claiming to answer "which vendor". Model names are matched with any vendor/ prefix stripped, so anthropic/claude-opus-4.6 and claude-opus-4.6 land in the same bucket.

  • Cost per line is only computed where file edits are recorded. Codex and Claude Code name the files a session edited; OpenCode and Hermes record tokens and cost but nothing about files. Their spend is excluded from every ratio rather than counted as cost with no work to divide by, their sessions are not counted as read-only, and the per-tool table marks them "Not recorded" instead of dropping them or ranking them as expensive.

  • A view with no recorded edits reports counts, not zeroes. When tracked tools ran but changed nothing, there is no denominator, so the panel shows session counts and spend rather than a cost of $0.00 that would read as free work.

  • Rework is measured as deletions over insertions across the window. A "churn" file is one the window left smaller than it found it. The rewritten-files table ranks by how many separate sessions touched a file, and spans every project at once, since file impact inside a single project's drilldown cannot show a file that is hard in three repos.

  • Spend that cannot be attributed is shown, not dropped. Some tools record an internal codename instead of a model name, and no lookup can resolve that. Those sessions are grouped under "Unidentified" with their share of spend stated, rather than being assigned to a guessed vendor or silently omitted.

  • Reasoning tokens are additive. They are billed as output and counted on top of the plain output figure, so the reasoning share in Work Patterns is a true fraction of the total. Tools that do not report a separate reasoning figure show "Not reported" rather than a misleading 0%.

  • When a tool records its own cost (OpenCode, Hermes), that recorded value wins for the session and no estimate is used.

  • Otherwise cost is priced per token component, because cached reads and output are not the same price as fresh input. Every session is normalized to four buckets: fresh input, cache reads, cache writes, and output.

  • Providers disagree on how they report cache reads. OpenAI (Codex) counts them inside input_tokens; Anthropic (Claude) reports them separately. codex-stats normalizes both conventions at ingest, so the cache ratio is always a real fraction between 0 and 1 and the four components always sum to the provider's own total.

  • A default rate table ships for known models, taken from each provider's published pricing page and converted from USD per million tokens to USD per 1k. It is a dated snapshot: see RATE_SNAPSHOT_DATE and RATE_SNAPSHOT_SOURCES in src/codex_stats/config.py, and update it when published prices move.

    • OpenAI rates are standard processing, short context. OpenAI only bills explicit cache writes from GPT-5.6 onward; earlier models use implicit caching, so their cache-write rate is 0. Long-context (>272k) pricing is not modeled.
    • Anthropic rates are standard pricing with 5-minute cache writes (1.25x base input). 1-hour writes (2x), Batch (-50%), fast mode, and the 1.1x data-residency multiplier are not modeled.
    • Model names are matched exactly first, then with a provider prefix stripped, so anthropic/claude-opus-4.6 resolves to the same rates as claude-opus-4.6.
  • Any model that cannot be identified — most often a third-party alias such as a provider's internal codename — falls back to DEFAULT_FALLBACK_RATES, a mid-tier published rate rather than a flat rate. A flat fallback badly overestimates cache-heavy sessions, because cache reads are normally about 10x cheaper than fresh input. The dashboard labels these sessions ("N sessions on a fallback rate") rather than presenting a silently wrong number. Set default_usd_per_1k_tokens to use a single flat rate for them instead.

  • Override rates per model in ~/.config/codex-stats/config.toml:

    [pricing]
    # optional: replace the fallback for unidentifiable models with one flat rate
    # default_usd_per_1k_tokens = 0.003
    
    [pricing.model_usd_per_1k_tokens.gpt-5.4]
    input = 0.0025
    cached_read = 0.00025
    cache_write = 0.0
    output = 0.015
    
    # a single scalar still works and applies to all four components
    [pricing.model_usd_per_1k_tokens]
    some-alias-model = 0.004
    
    # a source rate overrides the model table
    [pricing.source_usd_per_1k_tokens]
    claude = 0.015
    
  • Output depends on local file formats remaining compatible.

Roadmap

The current priority list lives in docs/roadmap.md.

Shareable Assets

The dashboard exports JPG cards with names like:

These sample assets were generated from the current renderer so the docs match what the dashboard actually downloads.

Development

For local development from the repo:

python3 -m venv .venv
source .venv/bin/activate
python -m pip install -U pip setuptools
python -m pip install -e .

Run without installing:

PYTHONPATH=src python3 -m codex_stats

Metadata

Release files for codex-stats 1.13.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for codex-stats 1.13.0
File Size Uploaded
codex_stats-1.13.0.tar.gz 121.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for codex-stats 1.13.0
File Interpreter ABI Platform
codex_stats-1.13.0-py3-none-any.whl Python 3 none any Details

Total release size: 205.0 kB

Release files / codex_stats-1.13.0.tar.gz

Download URL codex_stats-1.13.0.tar.gz
Size 121.3 kB
Tags Source
SHA-256 checksum
How to use checksums
6ce3dc79efe333bda6b745ad7e31db7295f5d7a73fd107c8c80fd2d51b47cdc8
BLAKE2b-256 checksum
How to use checksums
fc6e6400cf334f9c695e771eb31ab7d2517ddbd1771830a6414c4f9d7bdf8776
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 4, 2026.

Transparency log

Release files / codex_stats-1.13.0-py3-none-any.whl

Download URL codex_stats-1.13.0-py3-none-any.whl
Size 83.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
b6d48b3ef121225f60582d7059fef4243e61baebbd75220a18dec778969f6e50
BLAKE2b-256 checksum
How to use checksums
260264f157183f1b1e103915510c5199503b86e62c6563357ff6dacdc1212b0d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 4, 2026.

Transparency log

Release history Release notifications | RSS feed

This release

1.13.0 This release

2 release files

1.11.3

2 release files

1.11.2

2 release files

1.10.0

2 release files

1.9.0

2 release files

1.8.0

2 release files

1.7.0

2 release files

1.6.2

2 release files

1.6.1

2 release files

1.6.0

2 release files

1.5.9

2 release files

1.5.8

2 release files

1.5.6

2 release files

1.5.5

2 release files

1.5.4

2 release files

1.5.3

2 release files

1.5.1

2 release files

1.5.0

2 release files

1.4.3

2 release files

1.4.2

2 release files

1.4.1

2 release files

1.3.0

2 release files

1.1.0

2 release files

1.0.1

2 release files

1.0.0

2 release files

0.3.0

2 release files

0.2.0

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page