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Rank rows by a numeric column

dataset_top

The highest (or lowest) rows of the TakeoffDeck 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. It mentions ranking by a numeric column but does not disclose the limit parameter's role, default ordering, whether the operation is read-only, or the output format. The phrase 'highest (or lowest) rows' hints at sorting but omits key behavioral details.

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, concise sentence with the core action front-loaded. The appended phrase 'which is the most/least X' is slightly redundant but not harmful. It is appropriately sized.

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 simple read tool, the description lacks essential details such as how 'limit' affects the result and what the output looks like (full rows? subset of columns?). Without an output schema, the agent must infer the return structure. The description does not mention default ordering or error cases, making it incomplete.

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?

The description adds that the column must be numeric, which is helpful, but it does not explain the 'limit' parameter (number of rows to return) or the default behavior of 'ascending'. With only 33% schema coverage, the description should compensate for the undocumented 'column' and 'limit' parameters, but only partially does.

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, identifying the resource (TakeoffDeck dataset) and the action (return highest/lowest rows). It is distinct from sibling tools like dataset_search, dataset_stats, etc., which serve different purposes.

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?

The description implies a use case ('which is the most/least X') but does not explicitly mention when to choose this over alternatives like dataset_search or dataset_stats. There is no guidance on when not to use it or what conditions make it appropriate.

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

A4/5.0
Disambiguation4/5

Each tool targets a distinct querying need: schema, provenance, exact match, substring search, comparison, statistics, and top/bottom ranking. Dataset_row and dataset_compare could be confused for single-value lookups, but their stated purposes (exact equality vs. X/Y comparisons) make them distinguishable.

Naming Consistency5/5

All tools follow a consistent dataset_ prefix with lowercase snake_case naming. Although the second token mixes nouns and verbs, the pattern is highly predictable and easy to infer.

Tool Count5/5

Seven tools is well-scoped for a read-only dataset querying server. Each tool covers a distinct query mode without unnecessary redundancy or bloat.

Completeness5/5

For the apparent domain of exploring and querying a single dataset, the surface is complete: schema discovery, provenance, exact lookup, search, comparison, statistics, and ranking are all covered. No obvious read-only query operations are missing.

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