Diagnose Claude Code token usage and quota limits
tare teaches Claude Code to read its own logs so you can ask in plain English where your usage limit went, with no dashboards.
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Why it matters
Help developers understand where their Claude Code tokens and quota are going by analyzing local request logs, identifying expensive context patterns, detecting background automation, and explaining why usage limits were hit-all through natural language questions.
Outcomes
What it gets done
Analyze Claude Code logs to show which projects, files, or tools consumed the most tokens
Detect automation patterns like parallel sessions or background processes eating quota
Calculate rolling 5-hour window usage to predict if it's safe to start large tasks
Generate shareable usage reports with private data redacted for public posting
Source
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Overview
Tare
tare teaches Claude Code to read its own request logs and answer plain-English questions about where usage went, deduplicating inflated log counts and attributing context cost to the tool that caused it. It runs entirely locally with no network connections. Reach for it whenever a Claude Code usage limit hits unexpectedly, or to check quota attribution or rolling-window status before starting a big task.
What it does
tare teaches Claude Code to read its own request logs so you can ask, in plain English, where your usage went instead of digging through dashboards. It corrects for what a raw token count gets wrong: Claude Code's log format repeats each API response several times over, so naive counting inflated totals by 86% on the data it was built against, and tare deduplicates properly. It also charges tools for the context they caused, not just what they returned, since a file read early in a long session gets re-sent with every later message - which is how one big early read can quietly dominate a week. It tracks the rolling usage window (limits do not reset when you walk away; work from four hours ago still counts) and recognizes the signature of automation - hundreds of short parallel sessions is a script, not a person, and tare says so.
Ask it questions like "Why did I hit my usage limit yesterday?", "Which of my projects is eating my quota?", "Are my MCP servers adding a lot to my context?", or "Is it safe to start a big refactor now?" - the wording does not matter, complaining about limits is enough. /tare runs the full diagnosis; variants cover an at-a-glance panel (/tare usage), rolling-window status (/tare window), an HTML report (/tare report [days]), context breakdown (/tare tools [days]), a week-over-week comparison (/tare week), and a redacted, shareable summary (/tare share [days]). Answers come back as a cause, not a wall of numbers - for example, identifying that 99% of a day's usage came from a background tool that spawned over a thousand short sessions rather than the user's own work - followed by evidence and what to change; when usage is actually normal, it says that instead of manufacturing a finding.
When to use - and when NOT to
Use it whenever you hit a Claude Code usage limit unexpectedly, want to know which project, model, file, or MCP server is consuming quota, want to check whether it is safe to start a big task before your rolling window clears, or want to verify an automation or background process is not quietly running up usage while you are away. A shareable summary strips prompts, file paths/contents, commands, and session/account identifiers down to totals, dates, and tool names, so it is safe to post publicly or send to a colleague.
It currently reads only Claude Code's own logs, not other coding agents', and requires macOS or Linux (no Windows support yet) with Python 3.9+ (already present on every Mac, no packages to install). Everything runs locally with no network connections at all - do not take that on faith; SECURITY.md documents exactly what each script reads, writes, and sends, with a one-grep way to verify every claim yourself.
Inputs and outputs
Input is a plain-English question or a /tare slash command (with variants for usage, window, report, tools, week, or share); output is a diagnosis with evidence and a recommendation, an HTML report you open in a browser, a redacted shareable summary, or a CSV export.
Integrations
npx skills add kelviq/tare -g -y --copy --agent claude-code
No accounts, packages, or configuration beyond that one command; start a new Claude Code session and type / to confirm tare appears (a troubleshooting note in INSTALL.md covers machines where Claude Code has never installed a skill before, which can cause the installer to miss it). Team-wide and plugin-based install options are also documented in INSTALL.md. For developers, everything the skill does is also available as three dependency-free Python scripts with recipes for scripting, cron, CSV export, and live per-request telemetry (see CLI.md). MIT licensed.
Who it's for
Claude Code users who have hit a usage limit unexpectedly, or who want to know where their tokens actually go, without learning a dashboard or a command syntax.
Source README
tare
Ask Claude Code where your usage went.
You hit a usage limit and don't know why. Your quota drains faster than it
used to. You suspect something is eating tokens in the background. The
records that answer all of this are already on your computer - Claude Code
keeps a log of every request it makes. tare teaches Claude Code to read
its own logs, so you can just ask.
No dashboards, no commands to learn. Install once, then ask in plain
English.
Tare: the weight of the container, subtracted to find what's inside. Most
of what a session costs is the container - context re-sent again and again -
and that's exactly what these tools subtract.
Read full story - https://www.kelviq.com/blog/claude-code-usage-limits-where-tokens-go/
Install
One command, in any terminal:
npx skills add kelviq/tare -g -y --copy --agent claude-code
That's it. Nothing else to set up - no accounts, no packages, no
configuration. Start a new Claude Code session and it's live - type/ and check that tare appears. If it doesn't, see the
troubleshooting note - on machines where
Claude Code has never installed a skill before, the installer can miss
it. (Other ways to install - by hand, for a whole team, or as a Claude
Code plugin - are in INSTALL.md.)
Then just ask
Open Claude Code and ask your question the way you'd ask a person. These all
work - the words don't have to match, complaining about your limits is
enough:
When you hit a limit
Why did I hit my usage limit yesterday?
I got locked out ten minutes into my evening session - how is that
possible?
Did I hit the 5-hour limit or the weekly cap?
Why am I burning through my quota so much faster this week?
Where your tokens go
Where did my tokens actually go this week?
Which of my projects is eating my quota?
Which model is costing me the most?
What's the most expensive file Claude keeps re-reading?
How much did that giant session yesterday actually cost me?
Are my MCP servers adding a lot to my context?
How much overhead do subagents and skills add?
Before you start something big
How full is my 5-hour window right now?
Is it safe to start a big refactor now, or should I wait for my window to
clear?
Checking for things you forgot
Is something running Claude Code in the background?
Was Claude Code active while I was asleep?
I set up an automation last month - what is it costing me?
Tuning your setup
I started using /clear between tasks - did it actually help? Compare this
week to last.
Did the latest Claude Code update change my usage?
What would my usage cost if I were paying for the API directly?
What one change would save me the most?
Reports and sharing
Make me a usage report I can open in my browser.
Give me a summary I can post publicly - with nothing private in it.
Export my usage to a spreadsheet.
Prefer typing commands? /tare runs the full diagnosis, and takes variants
for the common asks - asking in plain words always works too:
/tare |
full diagnosis - where tokens went and why |
/tare usage |
at-a-glance panel - like /usage, with attribution |
/tare window |
how full is the 5-hour window - safe to start? |
/tare report [days] |
build the HTML report and open it |
/tare tools [days] |
what is filling my context |
/tare week |
compare this week with last |
/tare share [days] |
redacted summary safe to post publicly |
/tare why did I hit the limit yesterday |
any question works as the argument |
What you get back
Not a wall of numbers - a cause. The answer to "why did I hit my limit
yesterday?" looks like this:
99% of yesterday's usage came from a tool you're running, not from you.
Something spawned 1,553 short Claude Code sessions in your website project
- 9,022 requests, up to 51 sessions running at once. Your own hands-on
work that day was 93 requests. Each fresh session rebuilds its context
from scratch, which is the most expensive way to spend tokens...
...followed by the evidence, what to check, and what to change. And when
everything is actually fine, it says that: usage proportionate, no anomaly,
here's what's normal for you.
Real output lives in examples/ - a shareable summary produced
by /tare share, and the HTML report.
What it knows that a raw token count doesn't
- Correct totals. Claude Code's log format repeats each API response
several times over; naive counting inflates totals - by 86% on the data
this was built against. tare deduplicates properly. - The real cost of context. A file read early in a long session gets
re-sent with every later message. tare charges tools for what they
caused, not just what they returned - which is how one big file read
early can quietly dominate a week. - The rolling window. Limits don't reset when you walk away; work from
four hours ago still counts. tare can tell you how full your window was at
the exact moment you were locked out. - The shape of automation. Hundreds of short parallel sessions is a
script, not a person. tare recognises the signature and says so.
Private by design
Everything runs on your machine and nothing leaves it. The scripts make no
network connections at all. When you ask for a shareable summary, it
contains totals, dates and tool names only - no prompts, no file paths or
contents, no commands, no session or account identifiers - so you can post
it publicly or send it to a colleague and ask "what am I missing?"
Don't take that on faith: SECURITY.md states exactly what
each file reads, writes and sends, and shows how to verify every claim
yourself with one grep.
Requirements
- Claude Code on macOS or Linux
- Python 3.9+ - already present on every Mac; no packages to install
- Currently reads Claude Code's logs only, not other coding agents'
Demo
https://github.com/user-attachments/assets/358ecacb-972b-4452-9633-e530af3d5490
For developers
Everything the skill does, you can also do by hand: three dependency-free
Python scripts with recipes for scripting, cron, CSV export, live
per-request telemetry and more - see CLI.md.
Issues and PRs welcome. Useful directions: a live TUI, Windows paths,
aggregating anonymised summaries across users to spot patterns no single
person can see, and better token estimation for tool results.
MIT licensed.
FAQ
Common questions
Discussion
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