claudeusage
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- AlicenseNot gradedqualityBmaintenanceEnables offline, read-only forensic analysis of Claude Code session transcripts, providing exact token usage, cost estimates, context growth, and compaction suggestions.MIT
- AlicenseNot gradedqualityAmaintenanceReads the Claude Code, Codex and OpenCode usage logs already on your machine and reports token totals, per-day and per-hour activity, a per-agent and per-model breakdown, and a year-in-review recap. It makes no network request at all — a test fails if any source file in the package can open a socket.414MIT
- AlicenseNot gradedqualityCmaintenanceAnalyzes Claude Code session token usage and cost locally — where spend actually lands across cache-read, cache-write and output, and what is consuming the context window. Read-only and offline: it parses your own session files and exposes analyze_claude_cost, get_cost_benchmark and tokenscope_share_summary.27 npm4MIT
- AlicenseAqualityAmaintenanceToken usage and estimated cost for Claude Code, Codex, Cursor and 20 more AI coding agents, read locally from their session files. No API key, no telemetry.221AGPL 3.0
- AlicenseBqualityBmaintenanceLets a coding agent inspect its own run efficiency mid-session from local Claude Code transcripts, exposing the share of paid tokens that became model output versus context re-reading. Ships two stdio tools — one returning the shares as structured data and one returning the full cost-weighted report — with no network calls.2MIT
- AlicenseBqualityAmaintenanceLocal-first LLM cost analysis: measures spend from usage records and estimates savings from switching models, with prices you supply.394 npmMIT
TDQS
Scored across 4 tools
subscription_value and current_limits are clearly distinct, and the detailed descriptions make limit_breakdown and chat_share distinguishable as mechanism analysis vs. cross-product attribution. An agent skimming names alone could conflate the two rate-limit tools, but the descriptions resolve the ambiguity.
All four names are lowercase snake_case compound nouns, which gives the set a consistent shape. The convention is not verb_noun like typical action tools, and chat_share is a bit ambiguous semantically, but there is no jarring style mixing.
Four tools is compact but each one earns its place: local usage value, limit drivers, chat attribution, and live limit status. The server scope is narrow enough that this feels well-scoped rather than thin.
The set covers the core workflows: measuring local value, explaining limit consumption, attributing non-local usage, and querying current limits. The main gap is that current_limits can record samples to a log, but no tool reads that history back for time-series analysis.