dataset_topThe highest (or lowest) rows of the Walkvo dataset by a numeric column — "which is the most/least X".
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| column | Yes | ||
| ascending | No | true for the lowest first; default highest first |
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It adds the numeric-column requirement but mostly restates the ranking concept from the title. It does not disclose output format, default limit behavior, tie handling, or whether the returned rows are in sorted order.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single compact sentence with no filler, and the core highest/lowest concept is front-loaded. It is efficient, though the brevity contributes to under-specification in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description should clarify what the tool returns (e.g., rows, values, or counts) and how limit and ascending shape the result. It covers the numeric-column requirement but leaves the output format and ordering behavior undisclosed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 33%, and the description partially compensates: it clarifies that 'column' must be numeric and maps 'highest/lowest' to the ascending flag. However, it says nothing about 'limit' and relies on the schema for the ascending default.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The title and description clearly indicate the operation: return the highest or lowest rows of a dataset ordered by a numeric column. The 'most/least X' phrasing helps map natural-language ranking questions to this tool. It is distinct from siblings like dataset_row and dataset_stats, though it does not explicitly name them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Use is implied through 'which is the most/least X' for top-N/bottom-N questions, but there is no explicit statement of when to choose this tool over dataset_stats or dataset_search, and no exclusions or prerequisites are mentioned.
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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Each tool targets a distinct query type (schema, exact match, substring search, multi-value comparison, stats, top/bottom, provenance), but dataset_row and dataset_compare overlap for single-value exact matches, and dataset_columns' provenance banner overlaps somewhat with dataset_provenance.
All tools share the dataset_ prefix and snake_case, but suffixes mix nouns (columns, provenance, row, stats) with verbs (compare, search) and an adjective (top), so the pattern isn't as uniform as a strict verb_noun convention.
Seven tools is a well-scoped set for read-only dataset exploration; each operation (schema, lookup, search, compare, stats, top, provenance) earns its place.
Covers the core dataset workflows: schema, exact and fuzzy lookup, comparisons, numeric summaries, and attribution. Minor gaps like grouped aggregations or multi-condition filters are absent but not essential for the stated purpose.