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/dmdufresne/questllens/questllens-usingnpx skills add DMDuFresne/questllens --skill questllens-usinggit clone --depth 1 https://github.com/DMDuFresne/questllensWrote 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/dmdufresne/questllens/questllens-using)<a href="https://agentmods.dev/skills/dmdufresne/questllens/questllens-using"><img src="https://agentmods.dev/badge/skills/dmdufresne/questllens/questllens-using.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 | $0.00111 | $0.01114 |
| Opus 5 | $0.00056 | $0.00557 |
| Sonnet 5 | $0.00022 | $0.00223 |
| Haiku 4.5 | $0.00011 | $0.00111 |
Grade A, and why
questllens-using 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.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
questllens-using
Overview
questllens is a read-only lens onto a QuestDB instance: schema, partitions, storage, sample data, execution plans, and live ingestion diagnostics — 18 tools, all read-only. It cannot create a table, alter a parameter, resume a suspended WAL, cancel a query, or write a single row. This shapes every answer: questllens reports what is true of the database now; a human operator is the one who acts on it. This skill orients you and routes you to the right companion skill.
The read-only boundary is enforced by a SQL lexer, not a keyword filter. query accepts only
SELECT, WITH, EXPLAIN, SHOW, and TABLES, refuses anything after a ;, and rejects
write and admin verbs even inside CTEs and subqueries. Don't try to route around it — a
rejection is telling you to change the question, not the phrasing.
Time-series first, relational second
QuestDB is not Postgres with a timestamp column. Four concepts change how you write every query, and getting them wrong is the most common failure mode:
- Designated timestamp — the one column QuestDB partitions and orders by.
SAMPLE BY,LATEST ON, andASOF JOINare all undefined without it.list_tablesshows which tables have one;describe_tablenames it. - Partitions — data lives in per-DAY/HOUR/MONTH directories. A query without a time predicate scans all of them. Always bound the time range first, then filter.
- SYMBOL columns — interned strings, cheap to filter on and the intended way to express
device/sensor/instrument identity. They have a capacity; exceeding it degrades
performance silently.
describe_tablewithwith_symbol_stats=truereports distinct counts against capacity. - WAL — writes land in a write-ahead log and are applied asynchronously. A table can be accepting data while queries see stale rows. "The data isn't there" is often WAL lag, not missing data.
Discovery before guessing
Never write a query against a schema you haven't looked at:
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 · 81 lines · 111 tokens per session scan A a7abfafbce30
questllens-using is a skill published in the GitHub repository DMDuFresne/questllens (0 stars, last pushed 15d ago), licensed Apache-2.0. It adds 111 tokens to every session and 1,114 once invoked, about $0.0006 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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