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 akiotanaka847/qaio-desktop --skill ask-a-data-questiongit clone --depth 1 https://github.com/akiotanaka847/qaio-desktopWrote 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/akiotanaka847/qaio-desktop/ask-a-data-question)<a href="https://agentmods.dev/skills/akiotanaka847/qaio-desktop/ask-a-data-question"><img src="https://agentmods.dev/badge/skills/akiotanaka847/qaio-desktop/ask-a-data-question/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/akiotanaka847/qaio-desktop/ask-a-data-question"><img src="https://agentmods.dev/badge/skills/akiotanaka847/qaio-desktop/ask-a-data-question.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 | $0.00065 | $0.01563 |
| Opus 5 | $0.00032 | $0.00781 |
| Sonnet 5 | $0.00013 | $0.00313 |
| Haiku 4.5 | $0.00006 | $0.00156 |
Grade A, and why
ask-a-data-question 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 9d 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 — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ask A Data Question
When to use
User asked data question. Anything phrased "how many," "what's," "top N by," "trend of," "compare X to Y," "why did Z change." Translate to SQL, run safely, return result with citations.
Connections I need
I run external work through Composio. Before this skill runs I check the categories below are linked. Missing → I name the category, ask you to connect it from the Integrations tab, stop.
- Warehouse / data source (Postgres, BigQuery, Snowflake, Redshift) - Required. I run read-only SQL here. No warehouse means no answer.
If no warehouse is connected I stop and ask you to connect your warehouse first.
Information I need
I read your operations context first. For every required field that's missing I ask ONE plain-language question (best modality: connected app > file drop > URL > paste) and wait.
- Where the data lives - Required. Why I need it: I need to know which warehouse to query and the SQL dialect. If missing I ask: "Where does this data live? Best is to connect your warehouse from the Integrations tab and tell me which one to use."
- Cost ceilings - Optional. Why I need it: I warn before running anything that would scan more than your ceiling. If you don't have it I keep going with TBD and use a conservative default of 100 GB scanned.
- Table schemas - Optional. Why I need it: lets me draft accurate SQL without guessing column names. If you don't have it I introspect the warehouse on the fly.
- Operating context doc - Required. Why I need it: anchors what "this number looks weird" means against your priorities. If missing I ask: "Want me to set up your operating context first? Helps me catch suspicious results."
Hard rules
- Read-only. Any proposed query containing
INSERT,UPDATE,DELETE,MERGE,DROP,CREATE,ALTER,TRUNCATE,GRANT, orREVOKErefused immediately. - Warn before executing potentially expensive query. Use
warehouse explain / dry-run tool (discover via
composio search warehouse explainor provider equivalent) to estimate scanned bytes + runtime. Compare againstconfig/data-sources.json→costCeilingScannedGbandcostCeilingSecondsfor target source. If exceeded, state estimate, wait for explicit approval. - Every result ships with: exact SQL, run timestamp, row count, any data-quality caveats.
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.
- 9d ago First seen · 139 lines · 65 tokens per session scan A 89f55a35f685
ask-a-data-question is a skill published in the GitHub repository akiotanaka847/qaio-desktop (2 stars, last pushed 5d ago), licensed MIT. It adds 65 tokens to every session and 1,563 once invoked, about $0.0003 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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