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/tokenscope

Judgment-layer review of Claude Code token usage. Use when the user asks to audit token costs, review Claude Code spending, check context waste, or interpret a tokenscope report. Runs the tokenscope profiler, then interprets its findings with knowledge of the project's actual

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tokenscope
81 skill

Claude Code

$ npx -y skills add AviVAvi/TokenScope --skill tokenscope --agent claude-code

SKILL.md

tokenscope.SKILL.md
name: tokenscope
description: Judgment-layer review of Claude Code token usage. Use when the user asks to audit token costs, review Claude Code spending, check context waste, or interpret a tokenscope report. Runs the tokenscope profiler, then interprets its findings with knowledge of the project's actual workflow — separating mechanical waste from deliberate cost.

TokenScope review

You are the judgment layer on top of the tokenscope profiler. The CLI is a deterministic lookup table: it measures precisely but has **no model of the user's workflow** — it cannot distinguish "expensive because wasteful" from "expensive because verification is the product". Your job is to add that judgment.

Step 1 — Run the profiler

The tokenscope repo lives at `C:\Users\Asmit\OneDrive\bohra-labs\token-cost-mcp` (if moved, find it with Glob for `**/src/cli.ts` containing "tokenscope").

node <repo>/src/cli.ts              # overview: all projects, scores, top findings
node <repo>/src/cli.ts <name>       # one project: score breakdown + recommendations

If the user names a project, run the detail view for it. Otherwise run the overview and drill into the costliest or lowest-scoring project.

Step 2 — Gather workflow context (this is what the CLI cannot see)

For the project under review:

  • Read its `CLAUDE.md` and `.tokenscope.json` if they exist.
  • Skim the opening user prompts of 2-3 recent sessions in

`~/.claude/projects/<encoded-project-dir>/*.jsonl` (the first `"type":"user"` lines) to understand what kind of work happens there: coding tasks, planning/research, verification/adjudication, mixed.

  • Note any protocol the project follows (e.g. "verify against the repo, never

trust memory") — such protocols make some re-reading deliberate.

Step 3 — Interpret, don't parrot

Classify each CLI recommendation:

  • **Mechanical (apply-worthy):** environment notes from classified errors,

unused MCP servers, head/archive splits of append-only logs, codemap for code files. These are safe regardless of workflow.

  • **Intent-dependent (judge before recommending):**
  • *Re-read waste* — re-reads of actively-edited files, or reads mandated by

a verification protocol, are the protocol working, not waste. The fix for those is cheaper structure (head/archive split), never "skip the read".

  • *Output filtering* — NEVER recommend truncating output the project

measures or verifies against; a filtered count that returns 85 instead of 87 manufactures false confidence. Scope filtering to test runs/build logs.

  • *Session splitting* — long planning sessions may be paying for continuity

on purpose. Recommend splitting for task-shaped coding work only.

  • **Look for what the CLI missed.** Its detectors are thresholds. Check: are

hot files growing? Is one document serving as both current-state and history? Are many small reads actually one missing map (suggest `node <repo>/src/cli.ts codemap <dir>`)?

Step 4 — Deliver the review

Short, numbers-first: 1. Cost + score, and whether the score is fair for this workflow. 2. Apply today (mechanical items, with the ready-to-paste blocks). 3. Ignore, and why (intent-dependent items that score deliberate cost as waste). 4. What the profiler missed, if anything. 5. A `.tokenscope.json` proposal if recommendations misfire for this workflow (`{"verification": true, "mute": ["<rec-id>"]}`).

Rules

  • Every claim cites a measured number from the report or the transcripts.

Label anything else as judgment.

  • Never apply fixes without explicit approval. When approved: CLAUDE.md

blocks verbatim, real one-line summaries for key files (read just enough to write them), head/archive splits only with the user watching.

  • Never modify the tokenscope source as part of a review.
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Repo: AviVAvi/TokenScope

@avivavi
Ships withtokenscope

A token profiler for Claude Code. It parses the session transcripts Claude Code already writes to disk (~/.claude/projects/**/*.jsonl) and tells you where your tokens actually went — and what to change to spend fewer of them. ccusage tells you what you spent.

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Questions about tokenscope.

Which coding agents can use tokenscope?
tokenscope installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.