dataset_topThe highest (or lowest) rows of the Reconzy 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 |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavioral details by itself. It adds the numeric-column constraint and the highest/lowest behavior, but it omits how limit is applied, how ties or nulls are treated, whether validation fails on non-numeric columns, and what the returned rows look like. This is minimal disclosure for an unannotated tool.
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 one concise sentence with the key distinction front-loaded: highest/lowest rows by a numeric column. It contains no filler or needless repetition, though it could have used the available space to include more operational detail.
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?
Given the lack of annotations and output schema, the description does not fully equip an agent to call the tool correctly. It omits return format, limit behavior, and edge-case handling, and it provides no usage guidance relative to sibling tools. For a simple tool this is still below minimum viable completeness.
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 description coverage is only 33%, so the description must compensate for the undocumented parameters. It clarifies that column should be numeric and loosely maps ascending to lowest/highest, but it does not explain the limit parameter at all, nor does it state the default row count or how limit interacts with ranking. This is insufficient compensation for the schema gaps.
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 description clearly states that the tool returns the highest or lowest rows of the dataset based on a numeric column, and the phrase 'which is the most/least X' makes the intent concrete. It doesn't explicitly contrast with siblings like dataset_search or dataset_stats, but the extreme-ranking purpose is identifiable from the name, title, and description.
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?
There is no guidance on when to use this tool versus alternatives such as dataset_search, dataset_stats, or dataset_compare. The description implies a top/bottom-N ranking use case, but it provides no exclusions, conditions, or alternative routing, leaving the agent to infer applicability.
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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Tools are mostly distinct, but dataset_row, dataset_search, and dataset_compare have overlapping row-filtering purposes. Descriptions clarify exact match vs. contains vs. any-of, so confusion is unlikely but possible.
All tools share the dataset_ prefix, but the suffix pattern is inconsistent: some are nouns (columns, provenance, row, stats, top) and some are verbs (compare, search). A more uniform verb_noun or noun_only convention would improve predictability.
Seven tools is a well-scoped set for dataset exploration, covering schema, provenance, lookup, search, comparison, statistics, and top-values queries without redundancy or bloat.
The toolset covers the main dataset exploration operations well, but it lacks explicit distinct-value or grouped-aggregation tools, which could be useful for fuller ad-hoc analysis. It is not severely incomplete.