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scherlok

scherlok

by rbmuller
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

check

Run a data-quality watch across all tables and return a CI-style pass/fail gate based on CRITICAL or WARNING anomaly severity.

Instructions

Run a watch over all tables and return a CI-style pass/fail gate.

fail_on is "critical" (default — fail only on CRITICAL) or "warning" (stricter — fail on WARNING or worse). Mirrors scherlok ci. Returns passed plus the severity counts the decision was based on. Like watch, it saves what it sees except a table with a CRITICAL anomaly, so a check failing on CRITICAL keeps failing until the data recovers, while one failing on a WARNING passes next time; verify saves nothing. With baselines locked, check saves no profiles either.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "check"
  }
}

Input Schema

NameRequiredDescriptionDefault
fail_onNocritical

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations at all, the description carries the burden and does a good job: it discloses the non-obvious side effect that `check` persists state except for tables with CRITICAL anomalies, and that it saves no profiles when baselines are locked. Missing only auth/permission or performance context, which is minor here.

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?

Purpose is front-loaded, then parameter semantics, then behavioral caveats — a sensible order. The persistence sentences are dense and nested ("saves what it sees except a table with a CRITICAL anomaly..."), costing a little readability, but little is wasted.

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

Completeness4/5

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

Covers purpose, gating semantics, and persistence behavior; the output schema already documents the `passed`/severity-counts return, so restating it is harmless. A brief note on which tables are in scope (all tables — no filter parameter exists) is implied rather than stated.

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

Parameters5/5

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

Schema coverage is 0% and the single parameter has no enum constraint in the schema, so the description fully compensates by defining both accepted values (`"critical"` default, `"warning"` stricter) and their exact decision thresholds.

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?

Opens with a specific verb and scope: "Run a watch over all tables and return a CI-style pass/fail gate." It also names the equivalent CLI command (`scherlok ci`) and distinguishes itself from `watch` and `verify`, so the agent can select it without opening the 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?

Explains the two operating modes via `fail_on` (default CRITICAL vs stricter WARNING) and contrasts persistence behavior with `watch` and `verify`, which effectively signals when to pick each. It stops short of an explicit "use X instead when Y" rule for the remaining siblings like `investigate` or `status`.

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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