dataset_topThe highest (or lowest) rows of the Yearendo 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 carries the full behavioral burden. It discloses that the tool ranks by a numeric column and supports both highest and lowest ordering. However, it does not mention tie-handling, behavior on non-numeric columns, null values, or what the returned rows look like, leaving some uncertainty.
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 that communicates the core behavior and the mental model ('most/least X'). It is slightly awkward with the dash and quote, but it contains no filler and is appropriately short.
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?
For a small tool with 3 parameters and no output schema, the description is adequate but not fully complete. It gives the key ranking behavior and mentions the numeric-column requirement, but it does not describe the return format or the limit semantics beyond what the schema already states.
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% since only 'ascending' has a description. The description adds meaning by clarifying that 'column' must be numeric, but it does not explain the 'limit' parameter or otherwise compensate for the schema's sparse parameter documentation.
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 identify the operation: ranking rows of the Yearendo dataset by a numeric column and returning the highest or lowest values. The phrase 'which is the most/least X' gives a concrete purpose. It does not explicitly contrast with siblings like dataset_stats or dataset_search, but the behavior is distinct enough to be inferred.
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 when to use the tool: when the user asks for the most or least values of some numeric field. However, it offers no explicit guidance on when not to use it or which sibling tool to prefer for related tasks such as search or summary statistics.
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 clear, distinct purposes: schema, search, stats, provenance, and top/bottom comparisons are unambiguous. The main ambiguity is between dataset_row and dataset_compare, since both retrieve rows by exact column values, but descriptions clarify that compare handles multiple values in a specific order.
All tools follow a consistent dataset_ prefix with clear, lowercase snake_case names. The naming pattern is predictable and easy to scan, with no mixing of styles or vague generic verbs.
Seven tools is a well-scoped set for a single-dataset server. Each tool covers a distinct common operation—schema, lookup, search, comparison, stats, top values, and provenance—without unnecessary bloat.
The toolkit covers the core read-only operations needed for exploring and querying the Yearendo dataset: schema discovery, exact match, substring search, ordered comparison, numeric stats, ranking, and attribution. Minor gaps like grouped aggregations or combined filters exist, but agents can usually work around them with existing tools.