TraceFrugal
Loading local usageGitHub ↗

UNDERSTAND → TRY → COMPARE → KEEP OR UNDO

Smaller context. Still useful answers.

Reading usage from this computer…

LOCAL OPTIMIZER

Apply a real setting. Compare. Restore.

Check your installed Claude version against official docs, back up one project's settings, and try a smaller MCP result limit. A fresh-session receipt confirms activation. Compare hourly usage and answer quality, then keep or restore.

tracefrugal optimize --project /path/to/your/project
Local optimizer setup and verified versions →
My question was short. Why is input so large?

Input means everything the model receives for this request.

1 · Your short question

It joins instructions, available tool definitions and retained history.

2 · The model generates a tool call

The code and arguments it generates are output for this request.

3 · The tool returns a result

The result becomes input to the next model request. Retained earlier answers also become input.

What you seeHow it is counted
A generated answer, code or tool-call argumentsModel output when generated; input again if retained in a later request.
A browser Result, file contents or command resultTool-returned data supplied as model input. It is not model-generated output.
A terminal diff, progress log or truncated previewScreen formatting does not establish billed tokens. Use provider usage receipts.

Illustration only: 100k input per request × request count. Real context grows, is trimmed or compacted. Cache hits lower the applicable rate but still count as input; reuse is not guaranteed.

Reduce oversized tool results and unnecessary round trips first. Preserve useful cached context. These logs do not measure the exact share of your question, instructions, schemas and history.

Official tool-calling flow ↗ · Official prompt-cache accounting ↗

Usage over time

Recorded input, cache, and output tokens.

Read chart values
01 · UNDERSTAND THE INPUT

Why so much input, and so little output?

CHECK THE EVIDENCE
02 · TRY ONE CHANGE

Improve the context, keep your model.

Choose one small instruction to test. The app does not change your model or reasoning effort.

Your sessions

Choose a session to see how each request grew.

Responses include tool loops and subagents. Tokens are the total processed across requests, including repeated context. Select a row for its identity, input distribution and cost formula.

ONE RULE · 24-HOUR OBSERVATION

Try a context rule

This creates rules/tracefrugal-context.md in your Claude config directory, usually ~/.claude. It applies across projects using that directory and adds a small instruction to context.

Start a new Claude Code session and verify the rule is loaded with /context. This is an instruction, not enforced output compression. The app records usage; it cannot prove Claude followed the rule.

The rule stays active after 24 hours until you remove it. Keep the app running for hourly updates, or reopen it to catch up from retained logs.

UNDO THE CONTEXT RULE

Remove the trial instruction?

Only the rule created by this trial is removed. Restore refuses if it was edited elsewhere. Your observations and satisfaction ratings remain in history.

Start a new Claude Code session so the removed instruction is no longer in context. This cannot refund calls or undo work Claude already performed.