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Rank rows by a numeric column

dataset_top

The highest (or lowest) rows of the Runwayze 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

B3/5.0
Behavior3/5

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 states the tool returns the highest or lowest rows, implying sorting and limiting. However, it does not disclose output format, error behavior, or edge cases like ties or non-numeric columns. It is a basic but non-contradictory disclosure.

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 idea. It is concise and free of fluff, earning its place. There is no unnecessary information.

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 simple ranking tool, the description provides the essential purpose but omits details like return format and any caveats. With no output schema and low parameter coverage, the agent may not know what to expect in the response. It is adequate for basic use but not fully complete.

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 description). The tool description does not explain the 'limit' or 'column' parameters beyond what the schema already provides. It implies ascending via 'highest/lowest' but does not explicitly link it to the parameter. Given the low coverage, the description should compensate but does not.

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 clearly states the tool ranks rows of the Runwayze dataset by a numeric column to answer 'which is the most/least X'. This distinguishes it from siblings like dataset_row (single row) and dataset_search (search). It names the resource and the verb, making the purpose specific. However, it does not explicitly contrast with dataset_stats, but the intent is clear enough.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives. The description does not mention any scenarios, exclusions, or alternative tools. An agent has to infer that this is for ranking rows, but there is no explicit when-to-use or when-not-to-use context.

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

A3.7/5.0
Disambiguation4/5

Each tool has a distinct role: schema, provenance, exact match, substring search, multi-value comparison, numeric stats, and top-N. There is some overlap between the row retrieval tools, but the descriptions clarify the matching semantics enough to avoid serious confusion.

Naming Consistency4/5

All tools share a consistent dataset_ prefix and are concise, but they mix noun-style names (dataset_columns, dataset_provenance, dataset_row, dataset_stats) with verb/adjective-style names (dataset_compare, dataset_search, dataset_top). The pattern is still predictable and readable.

Tool Count5/5

Seven tools is well-scoped for a read-only dataset query server. Each tool covers a distinct query mode or metadata need, so none feel redundant or excessive.

Completeness4/5

The tool set covers schema discovery, provenance, exact lookup, fuzzy search, multi-value comparison, numeric aggregations, and top/bottom ranking. A minor gap is the lack of a generic sample/all-rows or distinct-value exploration tool, but the core question-answering workflows are well supported.

Resources