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/groupbynpx skills add agenkin/telemetrydeck-analytics --skill groupbygit 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/groupby)<a href="https://agentmods.dev/skills/agenkin/telemetrydeck-analytics/groupby"><img src="https://agentmods.dev/badge/skills/agenkin/telemetrydeck-analytics/groupby.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 | $0.00024 | $0.00279 |
| Opus 5 | $0.00012 | $0.00139 |
| Sonnet 5 | $0.00005 | $0.00056 |
| Haiku 4.5 | $0.00002 | $0.00028 |
Grade A, and why
groupby 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
Groupby
Run a one-dimension breakdown. $ARGUMENTS starts with the dimension name and then any flags:
tdq groupby $ARGUMENTS
Examples:
- "License split for App_launched, last 30d" →
tdq groupby license --event App_launched --interval last-30d - "OS major-version breakdown by users, this month" →
tdq groupby majorSystemVersion --metric users --interval this-month - "License share vs. last period" →
tdq groupby license --event App_launched --interval last-30d --compare prior-period - "Top countries last week" →
tdq groupby countryCode --metric users --interval last-7d
If the user mentions "share" / "mix" / "split", compute percentages client-side from the result and include them in the summary. If they say "vs last month" / "trending", add --compare prior-period.
Always state what the metric represents: --metric count is event count (not users), --metric users is unique clientUser cardinality.
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 · 24 lines · 24 tokens per session scan A 0834ca8fdaf6
groupby is a skill published in the GitHub repository agenkin/telemetrydeck-analytics (2 stars, last pushed 4mo ago), licensed MIT. It adds 24 tokens to every session and 279 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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