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 jin-bo/agentao --skill duckdb-analystgit clone --depth 1 https://github.com/jin-bo/agentaoWrote 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/jin-bo/agentao/duckdb-analyst)<a href="https://agentmods.dev/skills/jin-bo/agentao/duckdb-analyst"><img src="https://agentmods.dev/badge/skills/jin-bo/agentao/duckdb-analyst/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/jin-bo/agentao/duckdb-analyst"><img src="https://agentmods.dev/badge/skills/jin-bo/agentao/duckdb-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00027 | $0.00335 |
| Opus 5.5 | $0.00011 | $0.00134 |
| Sonnet 5.5 | $0.00005 | $0.00067 |
| Haiku 4.5 | $0.00003 | $0.00034 |
Grade A, and why
duckdb-analyst 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
DuckDB Analyst
Conventions
- Data lives in
./data/*.parquet(a read-only mount). Never write there. - Use DuckDB — either the
duckdbCLI orpython -c "import duckdb; …". - Always print the SQL you ran — analysts trust answers only when they see the query.
- Cap queries to
LIMIT 1000by default. - Save intermediate results as
./cache-<slug>.parquetin the workdir.
Workflow
ls ./datato discover filesduckdb -c "DESCRIBE SELECT * FROM read_parquet('./data/X.parquet') LIMIT 0"to learn schema- Write the query and run it via
duckdb -c "..."or a short Python script - If the user wants a chart, follow the
matplotlib-chartsskill next
Guardrails
- If the underlying file is larger than ~10 GB, warn the user before scanning it
- Never suggest or run
DELETE/UPDATE/DROP— DuckDB on parquet can't anyway, but the LLM must still not suggest it
Example shell
duckdb -c "SELECT product, SUM(revenue) AS total
FROM read_parquet('./data/sales.parquet')
GROUP BY product ORDER BY total DESC LIMIT 1000"
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 · 35 lines · 27 tokens per session scan A 037691cea644
duckdb-analyst is a skill published in the GitHub repository jin-bo/agentao (310 stars, last pushed today), licensed MIT. It adds 27 tokens to every session and 335 once invoked, about $0.0001 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 2026-08-30.
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