claudeusage
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| subscription_valueA | Measures what Claude Code usage actually left behind. Edits are folded in time order, so only lines that survived to the end of the session count — code rewritten three turns later drops out. view: summary (surviving lines and cost), waste (rework, failures, rejections and context bloat priced in dollars), mix (cost by activity), files (per-file detail). scope=project requires project_path. |
| limit_breakdownA | Works out what drives the 5-hour and weekly rate limits. On a subscription the real constraint is the limit gauge, not dollars. Cache reads are most of the cost but weigh about 1/70 of fresh input against the limit, so saving money and saving limit are different skills. view: windows (burn per window), fit (per-model weights and multipliers), steps (every change point), weekly (7-day windows). |
| chat_shareB | Rate limits apply to the whole account, so claude.ai chat and the mobile app drain the same gauge while leaving no local trace — log-only tools undercount. This subtracts what local logs explain from what the gauge actually did, and checks that estimate against the per-product breakdown Anthropic returns. view: weeks (weekly summary vs. that ground truth), windows (per 5-hour window), sources (coverage of each data source). |
| current_limitsA | Asks Anthropic what is left right now: the 5-hour, weekly and per-model (Fable) limits, plus the per-product breakdown (Claude Code / chat / Cowork). Reads Claude Code's credentials from the macOS keychain and sends them only to api.anthropic.com. record=true appends one sample to data/usage-log.jsonl — the breakdown covers only the current weekly window and is gone once that window rolls over, so it is worth recording now and then. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
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.