dataset_topThe highest (or lowest) rows of the Weekrota 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?
No annotations are provided, so the description carries the full burden. It does not explicitly state that the operation is read-only, does not mention the default ordering (highest first), or clarify the role of the limit parameter. The behavior is only partially transparent.
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 concise sentence with a clarifying example. It contains no redundant information and is well-structured for quick comprehension.
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, but the description omits important context such as the return format, the effect of the limit parameter, and error behavior for non-numeric columns. It is adequate for basic usage but not fully complete given the lack of an output schema and annotations.
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 one of three parameters (ascending) has a schema description, yielding 33% coverage. The description mentions a 'numeric column' but does not explain the 'limit' parameter or the default value for 'ascending'. Since schema coverage is low and the description does not compensate, parameter semantics are under-specified.
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 state the tool's purpose: ranking rows of the Weekrota dataset by a numeric column to find highest or lowest values. The example phrase 'which is the most/least X' reinforces the intended use case, and the verb 'Rank' is specific.
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 implies usage for top/bottom N queries and provides a natural-language example, but it does not explicitly state when to prefer this tool over siblings like dataset_stats or dataset_search, nor does it mention any prerequisites (e.g., the column must be numeric).
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.
Each tool targets a different aspect of the dataset: schema, provenance, exact lookup, substring search, multi-value comparison, aggregation, and ordering. dataset_compare and dataset_row are somewhat similar since both filter on column values, but the descriptions clarify that compare handles multiple values while row handles a single exact match.
All tools follow the same dataset_ prefix convention with a lowercase noun or verb suffix: columns, compare, provenance, row, search, stats, top. The naming is uniform and predictable, making it easy to infer the purpose of each tool.
Seven tools is a well-scoped set for dataset exploration and querying. Each tool covers a distinct operation type, and none are redundant or unnecessary.
The set covers schema discovery, provenance, exact and fuzzy lookup, multi-value comparison, descriptive statistics, and top/bottom ordering. A minor gap is the lack of a tool to list distinct values or facets, but the core needs for answering questions about this dataset are well covered.