Gulliver

gulliver_check

Run data quality checks—unique keys, not-null, accepted values, ranges, freshness and row counts—on a table or query in one budget-checked scan, so you can trust data after a load.

Instructions

Data quality checks on one table or query, all in one aggregate scan (budget-checked, over budget returns block): unique keys, not-null, accepted values, numeric ranges, freshness, min rows and row-count change since the last check. Every check runs and is reported; status 'fail' means at least one failed. It stores the row count in the local .gulliver folder for the next max_change_pct comparison. Give at least one check. Use it after a load or before trusting data; use gulliver_diff to compare two versions.

Input Schema

Name	Required	Description
`fresh`	No	'column=24h': newest value must be at most this old.
`where`	No	Optional filter, e.g. "ts >= '2026-01-01'" (needed on partitioned tables).
`ranges`	No	'column=min:max' (either side may be empty).
`target`	Yes	Table name or a SELECT to check.
`unique`	No	Keys that must be unique; 'a,b' for a composite key.
`accepted`	No	Allowed values per column, as 'column=a\|b\|c'.
`min_rows`	No	Fail when fewer rows.
`not_null`	No	Columns that may not contain NULL.
`connection`	No	Connection name as listed by gulliver_status (from gulliver.toml or GULLIVER_DSN). Omit for the default connection.
`max_change_pct`	No	Fail when the row count moved more than this percent since the last check.

Output Schema

Name	Required	Description	Default
`status`	Yes
`next_step`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedv0.3.1Nov 3, 2026

changedInput schema / properties / accepted / description

Previous value: -"'column=a|b|c' allowed values."New value: +"Allowed values per column, as 'column=a|b|c'."

changedInput schema / properties / connection / description

Previous value: -"Connection name from gulliver_status. Omit for the default."New value: +"Connection name as listed by gulliver_status (from gulliver.toml or GULLIVER_DSN). Omit for the default connection."

changedInput schema / properties / not_null / description

Previous value: -"Column names."New value: +"Columns that may not contain NULL."

Changed3 schema fields changedv0.1.1Nov 3, 2026

addedOutput schema / properties

Added value: +{
+  "next_step": {
+    "type": "string"
+  },
+  "status": {
+    "enum": [
+      "ok",
+      "warn",
+      "block",
+      "needs_rehearsal",
+      "needs_approval",
+      "skipped",
+      "fail",
+      "error"
+    ],
+    "type": "string"
+  }
+}

addedOutput schema / required

Added value: +[
+  "status",
+  "next_step"
+]

changedOutput schema / title

Previous value: -"gulliver_checkDictOutput"New value: +"GulliverResult"

First observedv0.1.0Nov 1, 2026

TDQS

A4.6/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations (readOnlyHint=false, idempotentHint=false), it discloses the side effect that makes those hints true: the row count is persisted to the local .gulliver folder for the next max_change_pct comparison. It also discloses budget-checking behavior ('over budget returns block'), the all-checks-run guarantee, and how status 'fail' is derived. No contradiction with annotations, since the state change is local bookkeeping, not database mutation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with what it does and the enumerated checks, then budget behavior, then side effects, then usage. It is dense but each sentence carries information; the long opening sentence is slightly run-on and pushes the constraint 'Give at least one check' near the end.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 10-parameter tool with full schema coverage, annotations, and an output schema, the description covers the remaining gaps an agent needs: cost/budget behavior, the persistence side effect, the fail semantics, and when to prefer a sibling. Nothing essential to correct invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds two things the schema cannot: the minimum-one-check constraint ('Give at least one check') and the cross-call semantics of max_change_pct, whose previous row count is stored from an earlier invocation. The other nine parameters are left entirely to the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The first clause names a specific verb and resource ('Data quality checks on one table or query') and enumerates the exact check families (unique keys, not-null, accepted values, ranges, freshness, min rows, row-count change). It also distinguishes itself from gulliver_diff by naming that sibling explicitly, so an agent can choose without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives concrete timing guidance ('after a load or before trusting data') and routes comparison work to gulliver_diff. It does not address the other plausible alternatives (gulliver_lint, gulliver_preflight, gulliver_inspect), so the exclusion set is partial rather than complete.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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