Borrowing it
Nothing to install: this file belongs to aarora79/claude-code-usage-analyzer. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/aarora79/claude-code-usage-analyzer/main/.claude/skills/tokenomics-dashboard/SKILL.mdgit clone --depth 1 https://github.com/aarora79/claude-code-usage-analyzerWrote 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/aarora79/claude-code-usage-analyzer/tokenomics-dashboard)<a href="https://agentmods.dev/skills/aarora79/claude-code-usage-analyzer/tokenomics-dashboard"><img src="https://agentmods.dev/badge/skills/aarora79/claude-code-usage-analyzer/tokenomics-dashboard/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aarora79/claude-code-usage-analyzer/tokenomics-dashboard"><img src="https://agentmods.dev/badge/skills/aarora79/claude-code-usage-analyzer/tokenomics-dashboard.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00114 | $0.01145 |
| Opus 5.5 | $0.00046 | $0.00458 |
| Sonnet 5.5 | $0.00023 | $0.00229 |
| Haiku 4.5 | $0.00011 | $0.00114 |
Grade A, and why
tokenomics-dashboard 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 1mo 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tokenomics Dashboard Skill
Produce the self-contained HTML tokenomics dashboard for a chosen window of Claude Code usage, then present it to the user with a director-of-tokenomics commentary. This wraps the claude-usage-analyzer CLI, which fetches usage via ccusage, prices it from LiteLLM, and writes the dashboard to data/output/tokenomics-dashboard.html.
The one input: number of days
The skill takes exactly one input from the user: how many days of history to analyze.
- If the user already gave a number ("last 30 days", "past 2 weeks"), use it and skip the question.
- Otherwise ask, and only this: "How many days of history should I analyze?" Offer sensible options (7, 30, 90) and note they can enter another number.
- State plainly, before fetching: "I will get this data using the ccusage tool." ccusage reads Claude Code's local usage files; nothing is uploaded.
Do not ask about output paths, formats, or models. Those are fixed: the analyzer always writes to data/output/ and prices every model dynamically.
Workflow
Step 1: Confirm the window and compute the start date
Convert the number of days into a --since date in YYYYMMDD format. The analyzer's --since is an inclusive start date, so for "last N days" use today minus (N - 1) days. Get today's date from the environment context; do not guess it. Tell the user the resulting date range you will analyze.
Step 2: Run the analyzer (it fetches via ccusage)
From the repository root, run the CLI with a refresh so the window is re-fetched, not served from a stale cache:
uv run claude-usage-analyzer --since <YYYYMMDD> --refresh
- Announce that this uses
npx ccusage@latestunder the hood to read local usage data, then prices it from LiteLLM. - If
npx/ccusageis unavailable, the tool prints an actionable error; relay it and stop rather than inventing numbers. - The run writes
data/output/tokenomics-dashboard.html,claude-usage-report.md, andclaude-usage-analysis.json.
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.
- 1mo ago First seen · 69 lines · 114 tokens per session scan A 0c54c48ab7c7
tokenomics-dashboard is a skill published in the GitHub repository aarora79/claude-code-usage-analyzer (6 stars, last pushed 2mo ago), licensed MIT. It adds 114 tokens to every session and 1,145 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-08-31.
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