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ginsonko

ap-aesthetics

by ginsonko

ap_inspect_dataset

Read-onlyIdempotent

Inspect datasets for observation provenance, missing labels, and group/split leakage before calibration to ensure reliable analysis.

Instructions

Inspect observation provenance, missing labels and group/split leakage before calibration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
datasetYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered and the description is consistent with it. The description adds the diagnostic scope (the checks performed) but says nothing about return format, failure behavior, or cost, so it adds only modest value beyond the annotations.

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

Conciseness5/5

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

A single front-loaded sentence with no filler; the most decision-relevant information (what is inspected and the workflow position) comes first. Nothing is wasted.

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

Completeness2/5

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

For a tool whose only input is an opaque nested object and which has no output schema, the description leaves the agent unable to construct a valid 'dataset' argument or anticipate what the inspection returns. It is a helpful summary but not complete enough to invoke confidently.

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

Parameters2/5

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

There is one required parameter, 'dataset', a free-form nested object with schema description coverage of 0% and no property documentation at all. The description does not describe the expected shape, required fields, or format of that object, so it fails to compensate for the coverage gap.

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

Purpose4/5

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

The description names a specific verb ('Inspect') and the three things examined (provenance, missing labels, group/split leakage), which is far more informative than the bare name. It does not explicitly contrast itself with siblings such as ap_evaluate or ap_fit_calibration, so it falls short of a 5.

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

Usage Guidelines3/5

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

'before calibration' gives an implied placement in the workflow, which points the agent toward the calibration tools in the sibling list. However, it states no exclusions, prerequisites, or explicit alternative, so usage is only inferred rather than spelled out.

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