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/agenkin/telemetrydeck-analytics/maunpx skills add agenkin/telemetrydeck-analytics --skill maugit clone --depth 1 https://github.com/agenkin/telemetrydeck-analyticsWrote 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/agenkin/telemetrydeck-analytics/mau)<a href="https://agentmods.dev/skills/agenkin/telemetrydeck-analytics/mau"><img src="https://agentmods.dev/badge/skills/agenkin/telemetrydeck-analytics/mau.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 | $0.00023 | $0.00177 |
| Opus 5 | $0.00012 | $0.00088 |
| Sonnet 5 | $0.00005 | $0.00035 |
| Haiku 4.5 | $0.00002 | $0.00018 |
Grade A, and why
mau 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 5d 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.
What it actually says
MAU
Run the monthly-active-users recipe. Default: last 6 calendar months.
tdq mau $ARGUMENTS
Examples:
- "MAU for the last 12 months" →
tdq mau --months 12 - "MAU this year" →
tdq mau --interval this-year - "MAU month-over-month" →
tdq mau --interval last-month --compare prior-period
After the table prints, summarize in one paragraph: latest month's value, trend direction over the window, any month that stands out. Call out if the current month is partial (this-month / this-year compares partial-to-full).
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.
- 5d ago First seen · 21 lines · 23 tokens per session scan A 0e3adb8a1075
mau is a skill published in the GitHub repository agenkin/telemetrydeck-analytics (2 stars, last pushed 4mo ago), licensed MIT. It adds 23 tokens to every session and 177 once invoked, about $0.0001 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 2026-08-31.
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