Skip to main content
Glama

Rank rows by a numeric column

dataset_top

The highest (or lowest) rows of the Reqnix dataset by a numeric column — "which is the most/least X".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
columnYes
ascendingNotrue for the lowest first; default highest first

Schema Changelog

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

  1. First observed

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It only states the basic ranking behavior and does not cover edge cases like ties, null values, ordering stability, or whether the operation is read-only. It also omits any mention of potential side effects or prerequisites.

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?

The description is a single sentence, front-loaded with the core purpose and a clarifying quote. It is concise and to the point, though it could benefit from a brief note on default parameters without sacrificing brevity.

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 with three parameters and no output schema, the description leaves important gaps: no default limit, no indication of return format, and no discussion of edge cases like ties or missing values. The description is too sparse to fully guide an agent through correct invocation without additional information.

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?

Schema description coverage is only 33% (only 'ascending' has a schema description). The tool description adds minimal parameter context—'numeric column' hints at column type but does not explain 'limit' or default behavior, nor does it clarify the exact meaning of 'ascending' beyond the schema. The description does not compensate for the low schema coverage.

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 description clearly states the tool ranks rows by a numeric column and returns the highest or lowest rows, distinguishing it from sibling tools like dataset_stats (aggregates), dataset_search (filtering), and dataset_row (single row). The phrase 'which is the most/least X' provides a concrete use case.

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?

No explicit guidance on when to use this tool versus alternatives. The description implies a use case (ranking top/bottom rows) but does not mention when not to use it or point to specific sibling tools, leaving the agent to infer the appropriate context.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation4/5

Each tool targets a distinct query mode: schema, exact lookup, substring search, multi-value comparison, statistics, top/bottom ranking, and provenance. There is slight overlap between dataset_row, dataset_compare, and dataset_search, but their descriptions clarify exact, multi-value, and containing matches.

Naming Consistency5/5

All tool names share the consistent dataset_* prefix and follow a clear pattern of dataset_ plus the operation or target concept. This makes the set predictable and easy to scan.

Tool Count5/5

Seven tools is a well-scoped size for exploring a single dataset. Each tool covers a distinct query or metadata need without redundancy or bloat.

Completeness5/5

The tools cover the full dataset exploration lifecycle: schema discovery, provenance, exact row lookup, substring search, ordered comparison, numeric statistics, and ranking. There are no obvious dead ends for common questions about this dataset.

Resources