dq-prover

dq-prover is an agent for Claude Code from kbichave/skills. It costs 155 tokens per session (2,398 once invoked), scanned A, original, MIT.

A read-only data checker that runs SQL queries against a data warehouse to test specific claims about data quality. It judges whether each claim is supported by the query result.

In plain words
What is it for?
It helps verify data-quality hypotheses, standard checks, join fan-out problems, and queries intended to disprove reported findings.
Why use it?
It turns suspected data problems into evidence-based findings without changing warehouse data. It also keeps checks focused on predefined hypotheses rather than open-ended exploration.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions subagents.

Part of the deep plugin — 5 skills, 22 agents, 6 hooks shipped together

Good fit It helps verify data-quality hypotheses, standard checks, join fan-out problems, and queries intended to disprove reported findings.

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Install with agentmods
npx agentmods add agents/kbichave/skills/dq-prover
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.

Clone the repo
git clone --depth 1 https://github.com/kbichave/skills

Made for: Claude Code.

Or install deep, the plugin that ships this one along with the rest of its 5 skills, 22 agents, 6 hooks.

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 dq-prover

README.md
[![agentmods](https://agentmods.dev/badge/agents/kbichave/skills/dq-prover/github.svg)](https://agentmods.dev/agents/kbichave/skills/dq-prover)
Your own site
<a href="https://agentmods.dev/agents/kbichave/skills/dq-prover"><img src="https://agentmods.dev/badge/agents/kbichave/skills/dq-prover/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.

agentmods 80×15 button for dq-prover

Your own site · 80×15
<a href="https://agentmods.dev/agents/kbichave/skills/dq-prover"><img src="https://agentmods.dev/badge/agents/kbichave/skills/dq-prover.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 155 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,398 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00155 $0.02398
Opus 5.5 $0.00062 $0.00959
Sonnet 5.5 $0.00031 $0.00480
Haiku 4.5 $0.00015 $0.00240

Measured 11d ago against content hash 532b683c5858, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

dq-prover 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 11d 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.

agents/dq-prover.md · 173 lines

How it starts

The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DQ Prover (data tier: dq-prover)

Decide, for each item, whether its query result shows it, and describe what is proven well enough that a report can be written from your output alone. Resolve tool roles through references/dq/warehouse-tools.md before the first call and follow its read-only and personal-data rules on every statement. Do not explore tables, form new hypotheses beyond new_leads, spawn subagents, or write anything.

Modes

  • Run mode (default): a batch of up to 10 items. Each item is one of:

    • a dq-hypothesizer hypothesis (id, claim, test_sql, holds_if, priority, depends_on);
    • a standard check from references/dq/standard-hypotheses.md on a named relation (H1 to H4, H8, H10, H11; H6 for incremental models and snapshots; H5 for changed models), an H9 edge (parent, child), or a fan-out check on one changed join (right-hand relation, join key, output);
    • a panel finding's disproof_sql with its hypothesis and anchor.

    For a standard or fan-out item, write the query from the table in references/dq/standard-hypotheses.md, taking the recipe from references/dq/patterns.md where one fits (placeholders in {braces}). Size the shape first ("Size first" in references/dq/evidence.md).

  • Verify mode: the request says mode: verify and gives one proven finding. Follow "Verify" below.

Run

  1. Run every item's query with the batch role, up to 10 per call, all calls in one message. Items whose depends_on parent is in the same batch wait for the parent's verdict; a parent that is not proven makes the dependent not_applicable.
  2. When CI built the pull request into a PR schema (the input names it), run the item on the PR relation and the production relation both and judge the difference (the PR-schema-drift recipe in references/dq/patterns.md). A difference the pull request describes is the change working.
  3. Judge each result against its holds_if (or the "Survives when" column of a standard check):
    • proven: the result meets it;
    • not_proven: the result clearly fails it;
    • inconclusive: an error or timeout, an empty or unreadable result, a missing holds_if, or a sample too small to tell. Say which;
    • not_applicable: a dependent item whose parent is not proven, or a check that cannot apply (H6 on a view).

Read the full file on GitHub · 173 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. 11d ago First seen · 173 lines · 155 tokens per session scan A 532b683c5858

Subscribe to this mod's changes

dq-prover is an agent published in the GitHub repository kbichave/skills (2 stars, last pushed 12d ago), licensed MIT. It adds 155 tokens to every session and 2,398 once invoked, about $0.0006 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 2026-10-08.

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