agentburn
Local profiler: which usage window took you out, and where your agent's money goes
Open source Open in the app JSON README (API)
About
Local profiler: which usage window took you out, and where your agent's money goes
Details
- Kind
- MCP servers
- Topic
- No topic detected
- Publisher
- socialpranker
- Origin
- official
- Category
- ferramentas
- Transport
- local
- Version
- 0.14.0
- Stars
- 119
- Forks
- 2
- Open pull requests
- 2
- Last push
- 2026-09-07T15:01:40Z
- Repository state
- ativo
- Language
- Python
- License
- MIT
- Added
- 2026-08-29 03:02:15
- Updated
- 2026-09-06 07:00:38
- Origin id
io.github.Socialpranker/agentburn
README
<div align="center">
<img src="assets/wordmark.svg" alt="agentburn — where does your AI agent burn money, while you sleep?" width="420">
<br>
<a href="https://pypi.org/project/agentburn/"><img alt="PyPI" src="https://img.shields.io/pypi/v/agentburn?color=f7775a"></a>
<img alt="Python" src="https://img.shields.io/badge/python-3.9%2B-5ab0f7">
<img alt="zero deps" src="https://img.shields.io/badge/dependencies-0-7df0a8">
<a href="../../actions/workflows/tests.yml"><img alt="tests" src="../../actions/workflows/tests.yml/badge.svg"></a>
<a href="LICENSE"><img alt="MIT" src="https://img.shields.io/badge/license-MIT-8a949e"></a>
<br><br>
<img src="assets/demo.svg" alt="uvx agentburn — animated demo: the verdict, the peak usage window, why it burns, what to change" width="760">
<br>
**[Claude Code](#supported-agents) · [Codex CLI](#supported-agents) · [Gemini CLI](#supported-agents) · [opencode](#supported-agents) · [OpenClaw](#supported-agents) · [Hermes Agent](#supported-agents)** — one normalized core, local, read-only, zero dependencies
```
uvx agentburn
```
**[▶ Try it in your browser — no install](https://socialpranker.github.io/agentburn/)**
</div>
---
## You didn't run out on your average day
You ran out inside **one window**. On this machine that window was **5.4× the median one** — same person, same week, same subscription.
Your assistant's own logs already know which window it was and what filled it. Nothing else on your machine does: the built-in counter shows a total, your invoice shows a total, and neither says *which five hours took you out.*
```
⏳ agentburn limits — claude-code · rolling 5-hour windows
PEAK WINDOW Aug 04 12:45–17:45 · 555M weighted
opus 91% · sonnet 9% · cli 93% · subagent 7%
TYPICAL WINDOW 104M median of 83 active 5h slots
PEAK / TYPICAL 5.4× a wall is hit by the peak, not by the median
WHAT FILLS THE WINDOW
cache reads 64% · cache writes 25% · output 11%
```
One command, no account, nothing leaves your computer:
```bash
uvx agentburn # where it burns, and what to change
uvx agentburn limits # how fast you fill a usage window, and how long until the wall
uvx agentburn context # what long contexts cost — and what a /clear at 150k would have saved
```
## Two ways agents cost you, two questions
| If you pay… | what actually runs out | ask |
|---|---|---|
| **a subscription** (Claude Code Pro/Max) | the rolling usage **window** — the invoice is fixed, the wall is not | `agentburn limits` |
| **per token** (API keys, OpenClaw, Hermes) | **money**, mostly while you're asleep | `agentburn` |
Both read the same local logs. Neither invents a number the data doesn't contain.
<img src="assets/demo-limits.svg" alt="agentburn limits — peak window, typical window, what fills it" width="760">
### `agentburn limits` — the subscription view
Optimizing a subscription doesn't change your bill. It changes how far you get before you're cut off. That is a *window* problem, and windows need intra-session resolution — a single session routinely spans several of them.
- **Peak vs typical.** Your worst rolling 5-hour window against the median of your own active ones. The ratio is the finding: a wall is hit by the peak.
- **What filled it** — by model, by source (you / subagents / scheduled work), and by kind (cache reads vs cache writes vs output).
- **Measured against your own wall — automatically.** Anthropic doesn't publish the formula behind those allowances, so agentburn refuses to invent a threshold. But Claude Code writes the cut-off into the transcript itself (*"You've hit your session limit · resets 8:30pm"*), and every one of those moments is a measured ceiling. With several, the ceiling is their median:
```text
YOUR MEASURED CEILING
median of 35 cut-offs Claude Code recorded itself
ceiling 146M weighted tokens
peak window 137% of your ceiling
last 5h 16% of your ceiling
TIME TO WALL 2.7 h at the pace of the last 30 min
```
No cut-off in your logs yet? `--hit "2026-08-20 14:30"` names one by hand. A measured ceiling is remembered in `~/.agentburn/ceiling.json`, so the status line below knows it too.
- **Codex: the provider's own reading.** Codex CLI writes `rate_limits.used_percent` next to every request. agentburn pairs each reading with your weighted usage of the same window and takes the median — a ceiling from the provider's arithmetic, not from a cut-off. Treat it as an estimate: that percentage counts every device and app on the account, while your local rollouts are only part of it — and when Codex stops reporting a window (plan or client change), a later peak is flagged as measured on earlier windows, not sold as an overrun.
- **Time to wall.** Ceiling minus the current window, divided by the pace of the last half hour. The number you actually want while working.
- **The week, too.** The heaviest rolling 7-day span, how much of it this week already is, and a weekly ceiling when Claude Code recorded a weekly cut-off.
- **By project.** Sessions record their working directory; the peak window is split by it.
### `agentburn statusline` — the wall, live, inside Claude Code
One line, no colour, built for Claude Code's `statusLine`:
```text
⏳ 5h 63% · wall in 47 min · week 71%
```
```json
{ "statusLine": { "type": "command", "command": "uvx agentburn statusline" } }
```
Reads only the last three days of logs (the ceiling comes from the state file), so it stays cheap enough to run on every turn.
### `agentburn context` — what a long context costs
Every call re-reads its whole context, and on a subscription that re-reading *is* the window: a turn at 300k costs what three turns at 100k cost. Claude Code records the exact context size of every call, so this is measured, not modelled:
```text
📏 agentburn context — claude-code · what a long context costs
CALLS 156,226 median context 143K · p90 316K · max 704K
WHERE THE WINDOW GOES, BY CONTEXT SIZE
100–200k ██████············ 35% 59,780 calls
200–400k ████████·········· 43% 42,420 calls
>400k ██················ 11% 7,257 calls
IF YOU HAD RESTARTED AT…
/clear at 100K → 41% of the window not spent (108,573 calls were past it)
/clear at 150K → 26% of the window not spent (73,600 calls were past it)
WHAT A SKILL COSTS
handoff 7.96K per load × 226 = 1.8M
claude-api 33.6K per load × 14 = 470K
```
- **The `/clear` arithmetic** — the part of every call's context above a threshold, at the cache-read rate: the honest saving of a restart habit, assuming the same work in shorter sessions.
- **Skill costs, measured** — the context growth right after a lone `Skill` call, median of recent loads. Bundled skills never touch the disk; the transcript sees all of them.
- **By effort level** — how much of the window each `effort` setting took.
- Findings with a lever land in `agentburn fix`: the restart threshold, and the heavy skills.
### `agentburn commits` — what a commit cost you
Sessions record their working directory and branch; your repositories record when each commit landed. The usage between two consecutive commits is what the second one cost — read-only `git log`, nothing written:
```text
COSTLIEST COMMITS
124M 33_Thoforge 1f7a31a1 Aug 30 fix(ui): правки UX-аудита — раскладка, навигация
81.2M 33_Thoforge ad19bff7 Aug 28 feat(ui): цель над деревом и развилка в карточке
BY REPOSITORY
33_Thoforge 1.95M median · 287 commits · 1.52B total
```
Weighted tokens = tokens × *published* price ratios (cache read 0.1×, cache write 1.25×, output per model), normalized to one input token of the reference model. Every ratio is public; none of them is a guess about how the provider counts.
### `agentburn` — the money view
- **Where it burns** — by source: `cron` / `subagent` / `gateway:telegram|discord|whatsapp` / `cli`. Always-on ≠ free.
- **🌙 While you slept** — the overnight bill, isolated and named (`--night 23-7`).
- **Fixed overhead** — uncached input tokens per API call, per source, calibrated against a public benchmark.
- **Subagent rollups** — delegation cost chained back to the session that spawned it.
- **`agentburn why`** — behavioral forensics: re-read loops, retry storms, idle heartbeats, per-cron receipts, context thrash.
- **`agentburn fix`** — ready-to-paste config patches, dry-run by design.
## `agentburn fix` — findings become config, not advice
Not "consider a cheaper model" but the exact file and the exact lines. Patch generators exist **only** for levers verified against the agent's own source or documented configuration:
```text
🔧 agentburn fix — claude-code · DRY-RUN (nothing was changed)
1. Drop 2 MCP server(s) you never called
why : registered but not called once in the last 30d: blender-mcp, pixellab.
Every registered server ships its tool definitions with the context
of every session that loads it.
proposed:
claude mcp remove blender-mcp
2. Trim the always-loaded memory files (2,254 tokens)
why : loaded into every session's context and re-sent whenever the prompt
cache expires or the context is compacted — at least 3,565× this window.
```
| Agent | Verified levers |
|---|---|
| Claude Code | registered MCP servers (`~/.claude.json`, `.mcp.json`), always-loaded `CLAUDE.md` memory files, the session-restart threshold (measured), heavy skills (measured per load) |
| Hermes | per-job `model` / `enabled_toolsets` (`cron/jobs.py`), per-platform toolsets (`gateway/run.py`) |
| OpenClaw | `heartbeat.{every, activeHours, model, lightContext}` (`config/types.agent-defaults.ts`) |
There is no `--apply` on purpose: it's your agent's config. Paste it yourself, then prove the saving with `--save-baseline` → `--compare`.
## Why trust these numbers
Token trackers quietly disagree with each other (2–91× in public issue threads). agentburn takes the opposite stance:
- Numbers come from **the agent's own accounting**, read-only. No scraping, no proxies, no guessing.
- **One reply is counted once.** Claude Code writes one transcript line per content block, each carrying the same `usage`; summing lines inflates calls and tokens ~1.8×. agentburn deduplicates by `requestId` (found and fixed in 0.14.0 — earlier absolute totals from this tool were inflated by that factor; ratios were not).
- Provider-billed costs are shown as-is; estimates are marked `~`; mixed data is labeled mixed.
- **Where a price doesn't exist, none is invented.** Claude Code records no costs and subscription usage has no honest per-token price — so that adapter reports tokens and windows, never dollars.
- Sessions with messages but **zero recorded tokens** (known accounting gaps, e.g. [hermes-agent #12023](https://github.com/NousResearch/hermes-agent/issues/12023)) are detected: totals become an explicit **lower bound**, and fixing the accounting becomes recommendation #1.
- Result weights on agents that don't record them are labeled *estimates*, and only ever used to rank findings against each other.
## Speed
Transcripts are append-only, so they are parsed once. Each file's parse is cached under its size and mtime in `~/.agentburn/cache`, and a run reuses every file that hasn't changed:
| 30 days over 3.1 GB of Claude Code logs | |
|---|---|
| first run (parses everything, writes the cache) | ~190 s |
| every run after that | **~3 s** |
| cache size | 29 MB (0.9% of the logs) |
A file that grew is re-parsed and re-cached; nothing else is touched. `--no-cache` (or `AGENTBURN_NO_CACHE=1`) forces a full re-parse, `--clear-cache` deletes it. The cache is derived data — deleting it costs time, nothing else.
## Privacy
Everything runs locally and reads your logs **read-only**. No network calls, no telemetry, no accounts. The report is yours. The only commands that touch the network say so: `drift` GETs a public trends file, `--submit` opens a prefilled issue *you* review and send.
The parse cache in `~/.agentburn/cache` (mode 0700) holds the same tool names and truncated argument keys the reports show, derived from logs already on this machine — never message content. `--clear-cache` removes it.
## Why this exists
Always-on agents bill you around the clock — and their built-in counters only show totals:
> *"73% of every API call is fixed overhead — ~13.9K tokens of tool definitions and system prompt, resent every time."* — [hermes-agent #4379](https://github.com/NousResearch/hermes-agent/issues/4379)
> *"One entrant wrote about waking up to a **$47 surprise bill** from an overnight run — that's not an exotic failure, it's the default behavior of an unsupervised loop."* — [dev.to](https://dev.to/chintanonweb/hermes-agent-gets-smarter-every-day-so-does-the-bill-4i8o)
## How it compares
| | **agentburn** | ccusage | codeburn | built-in `/usage` |
|---|---|---|---|---|
| Usage **windows** (peak vs typical, what filled them) | ✅ | — | — | current window only |
| Ceiling measured from your own recorded cut-offs · time to wall · status line | ✅ | — | — | current window % |
| The price of long contexts · what a `/clear` would have saved · skill cost per load | ✅ | — | — | — |
| Cost per git commit | ✅ | — | — | — |
| Burn by *source* (cron · heartbeat · gateways · subagents) | ✅ | — | — | % only, 7 days |
| 🌙 the overnight bill, isolated | ✅ | — | — | — |
| Behavioral forensics (`why`: loops, retry storms, failed-run cost) | ✅ | — | — | — |
| Ready config patches (`fix`, verified levers) | ✅ | — | — | — |
| MCP server (the agent answers for its own bill) | ✅ | — | — | — |
| Totals / live blocks / many CLIs | basic | ✅ best-in-class | ✅ TUI, 25 providers | totals |
*ccusage and codeburn are excellent at what they do — agentburn deliberately starts where they stop ([ccusage scoped per-tool analysis out](https://github.com/ryoppippi/ccusage/issues/688)).*
## Supported agents
One normalized model, one adapter per agent. Run `agentburn` and every agent found on the machine gets its own report.
| Agent | Status | Data source | Notes |
|---|---|---|---|
| **Claude Code** | ✅ | `~/.claude/projects/**.jsonl` | tokens and **windows**, by design: no local costs, no honest per-token price for a subscription |
| **OpenClaw** | ✅ | `~/.openclaw/agents/*/sessions/sessions.json` | **heartbeat is its own category** — the famous one |
| **Hermes Agent** | ✅ | `~/.hermes/state.db` (+ optional request dumps) | costs from the agent's own accounting |
| **Codex CLI** | ✅ | `~/.codex/sessions/**/rollout-*.jsonl` | tokens and windows; the only agent that records the **provider's own usage %** with every request |
| **Gemini CLI** | ✅ | `~/.gemini/tmp/*/chats/session-*.json` | per-turn tokens incl. thoughts; working directory via `projects.json` |
| **opencode** | ✅ | `~/.local/share/opencode/opencode.db` | costs from the agent's own price list; free/self-hosted providers show tokens only |
Adapters are ~150 lines over a shared model — PRs for the next one welcome.
<div align="center"><img src="assets/architecture.svg" alt="architecture: agent data → adapters → normalized model → report/limits/why/fix/explain/doctor/mcp" width="780"></div>
## Everything else
<details>
<summary><b>🔌 <code>agentburn mcp</code> — your agent answers for its own bill</b></summary>
A zero-dependency MCP stdio server exposing `burn_report` / `burn_limits` / `burn_context` / `burn_commits` / `burn_why` / `burn_card`. Register it and ask *"where do you burn my money?"* — it profiles its own database and explains.
```bash
claude mcp add agentburn -- agentburn mcp
# Hermes / OpenClaw: add an stdio MCP server with command `agentburn mcp`
```
Prefer skills? There's a ready [`SKILL.md`](skill/README.md) for `~/.claude/skills/agentburn/` (or the Hermes/OpenClaw equivalents).
</details>
<details>
<summary><b>📤 <code>--share</code> — an anonymized card, safe to post</b></summary>
Categories, models and totals only; session titles, paths and content are excluded *by construction*. `--svg card.svg` renders the same card as an image.
```text
🔥 my claude-code agent · last 30d
3.01B tokens · 19,255 API calls
where it burns: cli 77% · subagent 23%
⏳ my peak 5h window: 555M weighted tokens — 5.4× my own median window
🌙 while I slept (00–08): 75.3M tokens — 3% of everything
— agentburn · local & private
```
</details>
<details>
<summary><b>📐 <code>--save-baseline</code> / <code>--compare</code> — prove the saving</b></summary>
Snapshot your pace, change the config, then `agentburn --compare` shows the delta — pace-normalized, so a 7-day baseline compares honestly with a 30-day window. Every recommendation becomes a testable promise.
</details>
<details>
<summary><b>🧭 <code>agentburn drift</code> — your spend × the world's direction</b></summary>
Are you paying for a model the world is leaving? Your side is computed locally; the world side is one read-only GET of [token-history](https://github.com/Socialpranker/token-history)'s public trend JSON (archived daily from OpenRouter's rankings). Nothing about you is sent anywhere; `--trends FILE` works fully offline.
</details>
<details>
<summary><b>🧠 <code>agentburn explain</code> — LLM interpretation, local-first</b></summary>
```bash
agentburn explain --model llama3.1 # local ollama — nothing leaves the machine
agentburn explain --llm https://openrouter.ai/api/v1 \
--model deepseek/deepseek-chat --yes-remote --lang ru
```
The default endpoint is localhost; a remote one requires `--yes-remote` and receives a **redacted** summary (titles → `session-N`, paths → basenames, content never present to begin with).
</details>
<details>
<summary><b>🩺 <code>agentburn doctor</code> + 🚨 sentinel mode</b></summary>
`doctor` names the broken combinations (provider × model × source) behind zero-usage and unpriced sessions, and generates a ready-to-paste upstream bug report — counters only.
Sentinel mode is a budget guard for server agents:
```bash
agentburn --agent openclaw --budget-night 5 --fail-over --no-color \
|| notify-send "🚨 agent is burning money at night"
```
</details>
<details>
<summary><b>📊 <code>agentburn rank</code> — the Burn Index (community percentiles)</b></summary>
Anonymous percentiles of *efficiency* — the benchmark volume-leaderboards can't be: nothing here rewards burning more. Joining is consent-by-click: `agentburn --submit` prints the exact anonymized payload (ratios and a coarse spend band — never raw volumes, titles or paths), then a prefilled GitHub-issue link that **you** open and submit. Percentiles need 5+ setups per metric before they mean anything.
</details>
## Related
[token-history](https://github.com/Socialpranker/token-history) — the macro view: daily archive of *which agents the world uses*. agentburn is the micro view: *where yours burns*.
## License
MIT
<sub>mcp-name: io.github.Socialpranker/agentburn</sub>
---
<div align="center">
**the token-\* family** · [token-history](https://github.com/Socialpranker/token-history) — which agents the world runs · **agentburn** — where yours burns
*if this saved you a window's worth of work, a ⭐ helps the next person find it*
</div>