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Compare rows side by side

dataset_compare

The rows of the Binstockly dataset whose column is any of the given values, in the order given — for "X vs Y" questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
columnYes
valuesYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It usefully reveals that rows are filtered by 'any of the given values' and returned 'in the order given', but it says nothing about read-only status, output shape, missing-value behavior, or limits beyond what the schema encodes.

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?

The description is a single efficient sentence that fronts the core selection semantics and then names the intended use case. There is no filler, redundancy, or unnecessary background.

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

Completeness3/5

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

For a two-parameter tool this is minimally viable, but with no annotations and no output schema, the description leaves ambiguity about what the agent will receive and how edge cases behave. The title hints at side-by-side comparison, but the description itself does not fully specify the return presentation or failure semantics.

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 description coverage is 0%, so the description must clarify the parameters itself. It does this by explaining that 'column' is the field to match and 'values' are the accepted values, including the significance of their order. It could add more detail about value formatting or case sensitivity, but the core semantics are present.

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 identifies the resource (Binstockly dataset) and the operation as retrieving rows whose column matches any of the given values, preserving the provided order. The 'X vs Y' framing and title 'Compare rows side by side' distinguish it from sibling tools like dataset_row or dataset_search. It relies somewhat on the title for the verb, so it stops 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 Guidelines4/5

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

The phrase 'for "X vs Y" questions' gives a clear intended use context. However, it does not name alternative sibling tools or state when not to use this tool, so an agent must infer routing from the sibling list rather than being explicitly directed.

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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TDQS

A3.9/5.0
Disambiguation4/5

Each tool has a distinct role: schema, provenance, exact lookup, substring search, row comparison, summary stats, and top/bottom ranking. The only minor overlap is between dataset_row and dataset_compare for single-value exact matches, but the descriptions clarify their intended use cases.

Naming Consistency5/5

All tools follow the same dataset_ prefix with concise, lowercase, underscore-separated names. The naming pattern is highly predictable and makes the tool surface easy to scan.

Tool Count5/5

Seven tools is well-scoped for a read-only dataset exploration server. Each tool covers a meaningful querying or metadata need without redundancy or bloat.

Completeness4/5

The tool set covers schema inspection, provenance, exact matches, substring search, comparisons, numeric statistics, and top/bottom rankings. A general paginated 'list all rows' capability is missing, but agents can work around it using search or compare tools.

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