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 skills add agenkin/telemetrydeck-analytics --skill querygit 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/query)<a href="https://agentmods.dev/skills/agenkin/telemetrydeck-analytics/query"><img src="https://agentmods.dev/badge/skills/agenkin/telemetrydeck-analytics/query/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/agenkin/telemetrydeck-analytics/query"><img src="https://agentmods.dev/badge/skills/agenkin/telemetrydeck-analytics/query.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 | $0.00047 | $0.00364 |
| Opus 5.5 | $0.00019 | $0.00146 |
| Sonnet 5.5 | $0.00009 | $0.00073 |
| Haiku 4.5 | $0.00005 | $0.00036 |
Grade A, and why
query 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.
What it actually says
Query
Run raw TQL against the current app. Two ways:
(a) Inline JSON from $ARGUMENTS — pipe it to tdq query -:
echo '$ARGUMENTS' | tdq query -
(b) JSON file path — pass the path directly:
tdq query $ARGUMENTS
Pick (b) if $ARGUMENTS looks like a file path, else (a).
Writing the TQL
Before writing the JSON, read skills/analytics/tql/index.md in this plugin to route to the right sub-reference (filters, aggregators, intervals, funnel, retention, recipes, etc.). Do not try to recall TQL syntax from memory — the progressive-disclosure tree is there for a reason.
Rules that always apply:
- Set
"filter": { "__auto_app_and_test_mode_filter__": true }unless you need a custom filter (in which case include theappID+isTestMode=falseselectors yourself). - Every query needs
queryTypeandgranularity. - Prefer
userCount/thetaSketchover deprecatedcardinality.
If the user's first query returns (no rows), re-run with --raw to see whether the result is genuinely empty or the parser dropped it:
tdq query /tmp/q.json --raw 2>/tmp/raw.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 · 38 lines · 47 tokens per session scan A 474e97df399d
query is a skill published in the GitHub repository agenkin/telemetrydeck-analytics (2 stars, last pushed 6mo ago), licensed MIT. It adds 47 tokens to every session and 364 once invoked, about $0.0002 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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