Claude Code Skills Marketplace is a collection and marketplace of skills, plugins, agents, and instructions that extend Claude Code with specialized development workflows. It is for developers who want to install existing workflows or create, validate, and package their own Claude Code skills.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/daymade/claude-code-skills/claude-usage-analystnpx skills add daymade/claude-code-skills --skill claude-usage-analystgit clone --depth 1 https://github.com/daymade/claude-code-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/daymade/claude-code-skills/claude-usage-analyst)<a href="https://agentmods.dev/skills/daymade/claude-code-skills/claude-usage-analyst"><img src="https://agentmods.dev/badge/skills/daymade/claude-code-skills/claude-usage-analyst.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00091 | $0.00621 |
| Opus 5 | $0.00046 | $0.00311 |
| Sonnet 5 | $0.00018 | $0.00124 |
| Haiku 4.5 | $0.00009 | $0.00062 |
Grade A, and why
claude-usage-analyst scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
-
Verify
ccusageis available:ccusage --versionIf missing, install or update with
npm install -g ccusage@latestor run withnpx ccusage@latest. -
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/ShanghaiDefault
--since/--untilis today in the selected timezone. For historical comparison, set--sinceto an earlier date such as the first day of the month; otherwise rank/median fields only describe the single target day. -
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 -
Read
references/explanation-guide.mdwhen writing the final answer.
Evidence Rules
- Base numeric claims on
ccusageoutput or the bundled analyzer output. - State the scope:
ccusage claudemeasures 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.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 56 lines · 91 tokens per session scan A 2937e96ac368
claude-usage-analyst is a skill published in the GitHub repository daymade/claude-code-skills (1,377 stars, last pushed yesterday), licensed MIT. It adds 91 tokens to every session and 621 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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