| name | claude-usage-analyst |
| description | Analyze Claude Code and Claude Desktop Code token usage, cost, quota burn, model mix, cache read/write, and 5-hour block consumption using ccusage evidence. Use when the user asks why Claude quota was exhausted, whether a model such as fable/opus/sonnet is unusually expensive, how many tokens were spent today or historically, or needs a human-friendly explanation of local Claude Code CLI/Desktop usage. |
Claude Usage Analyst
Overview
Use this skill to produce evidence-based usage explanations from local ccusage data. Separate observed numbers from interpretation, and explain quota burn in human terms.
Workflow
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Verify ccusage is available:
ccusage --version
If missing, install or update with npm install -g ccusage@latest or run with npx ccusage@latest.
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Run the bundled analyzer for the requested window:
python3 /path/to/claude-usage-analyst/scripts/analyze_claude_usage.py \
--since YYYY-MM-DD --until YYYY-MM-DD --timezone Asia/Shanghai
Default --since/--until is today in the selected timezone.
For historical comparison, set --since to an earlier date such as the first day of the month; otherwise rank/median fields only describe the single target day.
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If the user asks about a specific model comparison, pass aliases:
python3 scripts/analyze_claude_usage.py --model-a fable --model-b opus-4-8
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Read references/explanation-guide.md when writing the final answer.
Evidence Rules
- Base numeric claims on
ccusage output or the bundled analyzer output.
- State the scope:
ccusage claude measures local Claude Code usage logs, including Claude Desktop's Claude Code sessions when those local logs exist. It is not a complete ordinary Claude.ai chat bill.
- Report dates with timezone.
- Explain cache clearly: cache read tokens are still usage/quota pressure even though the user did not type those words.
- Do not infer Anthropic plan quota rules from local token counts unless the user provides plan details. Say "quota-like pressure" or "ccusage estimated cost/token burn" when exact plan accounting is unknown.
- When comparing models, compare both token volume and estimated cost. A model can have similar token volume but higher cost.
Output Shape
Use this structure unless the user asks otherwise:
- Short conclusion in plain language.
- Evidence table: total tokens, cost, input, output, cache create, cache read.
- Model comparison table.
- 5-hour block table when quota exhaustion is discussed.
- Explanation of why the burn happened.
- Confidence and caveats.
Keep the answer readable for non-technical users. Avoid unexplained terms like "cache read" without a one-sentence translation.
