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Rank rows by a numeric column

dataset_top

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

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "column": "<column>"
    },
    "name": "dataset_top"
  }
}

Input Schema

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

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does not mention that this is a read-only operation, whether results are sorted (obvious from 'highest/lowest' but not explicit), how ties are handled, or what the return format is (e.g., list of rows). It also fails to disclose default behaviors for parameters like limit or ascending, which are only partially captured in the schema. The description adds minimal behavioral context beyond the core ranking concept.

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, concise and to the point. It front-loads the core purpose ('highest (or lowest) rows') and uses a clear example ('which is the most/least X'). However, it could be more structured by explicitly mentioning the limit and ascending parameters to aid comprehension, but it is not overly verbose or padded.

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?

Given the tool has 3 parameters, no output schema, and no annotations, the description is insufficiently complete. It does not specify the return format (likely a list of rows), default values for limit and ascending, error conditions (e.g., non-numeric column), or edge cases like ties. An agent would need to infer or test these behaviors. The description is too brief to fully support correct invocation.

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

Parameters3/5

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 description adds meaning to the 'column' parameter by specifying it must be numeric ('by a numeric column'), which is helpful. However, it does not clarify the 'limit' parameter's semantics or default behavior, nor does it elaborate on 'ascending' beyond what the schema already states. It partially compensates for the low coverage but leaves the limit parameter under-explained.

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 by a numeric column and identifies highest or lowest, answering 'which is the most/least X'. It is specific enough to distinguish from siblings like dataset_row (fetches a single row) and dataset_search (searches), though it doesn't explicitly name alternatives. The phrase 'highest (or lowest) rows' is slightly ambiguous about the number of rows returned, but the verb 'rank' and resource 'dataset' make the core purpose clear.

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?

No explicit guidance on when to use this tool versus siblings. There is no mention of alternatives like dataset_search for filtering or dataset_stats for aggregations. The description implies a use case (finding top/bottom rows) but provides no exclusions or conditions, leaving the agent to infer when this tool is 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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