questllens-using

questllens-using is a skill for Claude Code, Codex from DMDuFresne/questllens. It costs 111 tokens per session (1,114 once invoked), scanned A, original, Apache-2.0.

A read-only guide for using QuestDB, a database designed for time-based data, through the questllens server. It explains how to inspect schemas, partitions, storage, sample data, query plans, and ingestion health.

In plain words
What is it for?
Inspecting QuestDB tables, timestamps, partitions, storage, queries, and live data-ingestion diagnostics.
Why use it?
It helps agents ask valid time-series queries while making clear that the server cannot change data or database settings.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Install

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.

agentmods
npx agentmods add skills/dmdufresne/questllens/questllens-using
Any agent
npx skills add DMDuFresne/questllens --skill questllens-using
Clone the repo
git clone --depth 1 https://github.com/DMDuFresne/questllens

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for questllens-using

README.md
[![agentmods](https://agentmods.dev/badge/skills/dmdufresne/questllens/questllens-using.svg)](https://agentmods.dev/skills/dmdufresne/questllens/questllens-using)
Your own site
<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>
Per session 111 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,114 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 5d ago against content hash a7abfafbce30, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

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.

skills/questllens-using/SKILL.md · 81 lines

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, and ASOF JOIN are all undefined without it. list_tables shows which tables have one; describe_table names 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_table with with_symbol_stats=true reports 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:

Read the full file on GitHub · 81 lines

Changes

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.

  1. 5d ago First seen · 81 lines · 111 tokens per session scan A a7abfafbce30

Subscribe to this mod's changes

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.

Related

Other skills, from other repositories

schema-exploration

Lists tables, describes columns and data types, identifies foreign key relationships, and maps entity relationships in a database. Use when the user asks about database schema, table structure, column types, what tables exist, ERD, foreign keys, or how entities relate.

langchain-ai/deepagents · 57 tokens

sdk-design

Doctrine for designing and evolving any SDK Grida ships — TypeScript, Rust, or otherwise. "SDK" here means a surface that crosses a foreign-or-foreign-treated boundary: published packages, separately-versioned consumers, FFI bindings, public-by-design modules. An SDK's job is to refuse; a strict, honest surface…

gridaco/grida · 199 tokens

ha-data-stores

Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…

shiwenwen/hope-agent · 115 tokens

supabase

Supabase / PostgREST Row-Level-Security playbook — pull the anon (or leaked servicerole) key out of the frontend JS, map tables from the auto-generated OpenAPI spec, test anonymous RLS READ disclosures (PII/secret leaks), and anonymous RLS WRITE abuse (insert/update/delete — e.g. forging…

PentesterFlow/agent · 120 tokens

nornicdb-cypher-queries

Pick fast, predictable Cypher query shapes in NornicDB — point lookups, batch retrieval, pagination, search, traversal, batched UNWIND/MERGE writes, cleanup, multi-tenant isolation. Use when writing or reviewing Cypher whose latency or throughput matters; maps user intent to the executor's hot-path query templates.

orneryd/NornicDB · 79 tokens

dsql

Build with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, diagnose cluster performance, load data, and develop applications with a serverless, distributed SQL database. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL and PostgreSQL-to-DSQL schema conversion, foreign key…

awslabs/agent-plugins · 229 tokens