dataset_topThe highest (or lowest) rows of the Orgbix 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?
The description states the core behavior (returning highest/lowest rows by a numeric column) and the ascending parameter indicates ordering direction. However, it does not mention default limit behavior, handling of ties or nulls, error conditions for non-numeric columns, or output format. Since there are no annotations, more behavioral disclosure would be expected.
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 brief and to the point, using a clear format with an example query. It avoids unnecessary detail while conveying the essential purpose. The structure is clean and easy to parse.
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?
The tool is simple and the description covers the main intent, but important contextual details are missing: no default for limit, no mention of output schema or row structure, and no error handling notes. Given the presence of sibling tools, a sentence on when to choose dataset_top would improve 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?
Only the ascending parameter has a description in the schema; column and limit lack descriptions. The tool description mentions 'numeric column' which hints at the column parameter, but limit is not explained at all. With only 33% schema coverage, the description does not sufficiently compensate for the missing parameter details.
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 the tool ranks rows by a numeric column and returns the highest or lowest values, with the example query 'which is the most/least X'. The title reinforces this purpose. It is easily distinguishable from sibling tools like dataset_search or dataset_stats.
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?
The description does not explicitly state when to use this tool versus alternatives such as dataset_stats or dataset_search. It provides an example question but no guidance on selection criteria or scenarios. Sibling tools are listed but no comparisons are made.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes: schema, provenance, stats, top, and three row-query modes. The row-query tools (dataset_row, dataset_search, dataset_compare) are the main source of ambiguity, though their descriptions do clarify the different match semantics.
All tools share the dataset_ prefix and use consistent snake_case, giving a clear family identity. The second part is not uniformly verb-based (columns, provenance, top vs. compare, search), but the pattern is still predictable and readable.
Seven tools is well-scoped for a read-only dataset-access server. Each tool covers a distinct query mode or metadata need without unnecessary redundancy.
The tool surface covers schema discovery, provenance, exact and fuzzy row lookup, comparisons, aggregations, and ranking, so most data-exploration questions are supported. Minor gaps include no general pagination through all rows and no distinct-values tool, but these are workaroundable.