<p align="center">
  <img src="https://raw.githubusercontent.com/arsentev-ai/contextburn/main/assets/readme/hero.svg" width="100%" alt="contextburn: real output over 24 hours — useful work 0.18% of tokens, context re-reading 98.4%, cost-weighted useful work 6.7%, one useful token costs 555 paid tokens">
</p>

<p align="center"><a href="https://doi.org/10.5281/zenodo.22712985"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.22712985.svg" alt="DOI 10.5281/zenodo.22712985"></a></p>

**contextburn** reads the transcripts Claude Code already writes on your machine and tells you what
share of the tokens you paid for became model output — and how much was the agent re-reading
context it had already sent.

Token counters answer *"how much did I spend?"*. This answers *"how much of it was work?"* — a
normalised share, so it can be compared across sessions, models and ways of working.

## Try it

```bash
cp bin/contextburn ~/bin/contextburn && chmod +x ~/bin/contextburn   # python3 only, no dependencies
contextburn detail 24
```

## Demo

<p align="center">
  <img src="https://raw.githubusercontent.com/arsentev-ai/contextburn/main/assets/readme/demo.gif" width="100%" alt="contextburn detail 72 over the 36 experiment runs: 168 sessions, useful work 1.44% of tokens, context re-reading 94.4%, cost-weighted 28.8%">
</p>

Real output over the session logs of the 36 runs behind the U-curve report — nothing else on the machine. Video with DOI: [10.5281/zenodo.22713920](https://doi.org/10.5281/zenodo.22713920). The runs themselves are open: [Hugging Face](https://huggingface.co/datasets/arsentev-ai/context-ucurve-coding-agents) (DOI 10.57967/hf/10366) · [Kaggle](https://www.kaggle.com/datasets/arsentevai/context-u-curve-of-coding-agents-36-runs) · [OSF](https://osf.io/5qtwy/) (DOI 10.17605/OSF.IO/5QTWY).

## Why two numbers

<p align="center">
  <img src="https://raw.githubusercontent.com/arsentev-ai/contextburn/main/assets/readme/two-numbers.svg" width="100%" alt="Same 12 tasks, one long session versus twelve short, 3 runs each: token efficiency 1.11% vs 1.12%, no difference; cost-weighted efficiency 31.6% vs 24.6%, seven points apart">
</p>

- **By tokens** the share barely moves. Every agent step resends the accumulated context, so
  re-reading dominates whatever you do — it describes the agent.
- **Cost-weighted** the share does move, because cached reads are priced far below fresh input and
  output. It depends on how you run sessions — it describes you.

The comparison above comes from a controlled experiment with its dataset and analysis scripts:
[Clear Every Third Task: A Measured U-Curve in the Context Economy of Coding Agents](https://doi.org/10.5281/zenodo.22699668).

## How it counts

- Reads local Claude Code transcripts (`~/.claude/projects/**/*.jsonl`). **Nothing leaves the
  machine — no network calls at all.**
- Deduplicates usage records by message id and keeps the element-wise maximum. A streaming runtime
  writes an early snapshot and a final record for the same call: counting both double-counts it,
  keeping only the first halves the output.
- Weights the cost share with per-model prices kept at the top of `bin/contextburn`. Update them
  there when they change.

## Commands

| command | what it shows |
|---|---|
| `contextburn` | what is burning tokens right now |
| `contextburn detail [hours]` | run efficiency, sessions, and what specifically inflated the context |
| `contextburn window` | the current 5-hour subscription window |
| `contextburn --json` | machine-readable state (used by the menu-bar app) |
| `contextburn --probe <hours>` | raw JSON dump of the parsed sessions |
| `contextburn --efficiency [hours]` | run efficiency as JSON |
| `contextburn mcp` | start the MCP server |

### Configuration

| setting | default | meaning |
|---|---|---|
| `CONTEXTBURN_LANG` or `~/.config/contextburn/lang` | `en` | interface language: `en` or `ru` |
| `CONTEXTBURN_DAY_START` | `6` | hour your day starts — the daily total resets here |
| `CONTEXTBURN_WARN` | `30000000` | tokens/hour that turns the menu-bar counter yellow |
| `CONTEXTBURN_ALARM` | `90000000` | tokens/hour that turns it red |

The language file exists because the menu-bar app is launched from Finder, where environment
variables never reach it: `echo ru > ~/.config/contextburn/lang` switches both the app and the CLI.

## MCP server

Let the agent read its own run efficiency mid-session. The package ships a dependency-free MCP
server (stdio) with two tools: `run_efficiency` returns the shares as structured data, and
`spend_breakdown` returns the full report.

```bash
claude mcp add contextburn -- uvx contextburn mcp
```

Or install it as a Claude Code plugin, which registers the same server:

```text
/plugin marketplace add arsentev-ai/contextburn
/plugin install contextburn@contextburn
```

<!-- mcp-name: ai.arsentev/contextburn -->
<!-- mcp-name: io.github.arsentev-ai/contextburn -->

## Editor extensions

- **VS Code-compatible editors (VSCodium, Cursor, Windsurf, Gitpod…)** — [Open VSX: arsentev-ai.contextburn](https://open-vsx.org/extension/arsentev-ai/contextburn). A status bar meter over the local CLI; source in [`editors/vscode`](editors/vscode).
- **Raycast** — source in [`editors/raycast`](editors/raycast), Store submission pending.

## Menu-bar app (macOS)

`app/main.swift` is a small status-bar app. It polls `contextburn --json` once a minute and shows the
current burn rate with an hourly graph; click a bar to see that hour's breakdown.

```bash
swiftc -O -o ContextBurn app/main.swift
```

Set `CONTEXTBURN_BIN=/path/to/contextburn` if the CLI is not in `~/bin` or the usual Homebrew paths.

## Limits

- Claude Code transcripts only, for now.
- The cost-weighted share is only as current as the price table in `bin/contextburn`.

## Citing

Software DOI (all versions): [10.5281/zenodo.22712985](https://doi.org/10.5281/zenodo.22712985). GitHub's **"Cite this repository"** button gives the
reference; metadata is in [`CITATION.cff`](CITATION.cff).

## Author

Evgenii Arsentev — [arsentev.ai](https://arsentev.ai) ·
ORCID [0000-0002-9120-7298](https://orcid.org/0000-0002-9120-7298)

This project was published as `tokmon` on its first day and renamed to avoid confusion with
unrelated tools of that name; `TOKMON_*` environment variables still work.

## License

MIT — see [LICENSE](LICENSE).