dataset_topThe highest (or lowest) rows of the Perdiemo 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, the description carries the full burden. It mentions sorting by highest/lowest but doesn't disclose handling of ties, null values, whether all columns are returned, or if the tool is read-only. The schema has no descriptions for column and limit, and the description adds little beyond the basic operation.
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 front-loads the primary purpose and includes a helpful example in plain language. It contains no filler, though it is arguably too brief to convey all necessary context.
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 with no output schema and no annotations, the description leaves critical gaps: it does not specify what the returned rows look like (all columns or just the ranking column), whether ties are broken, or whether only numeric columns are valid. An agent cannot fully predict the behavior from this description alone.
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% (only 'ascending' has a description). The description does not explain 'column' beyond implying a numeric column, nor does it clarify 'limit'. It adds no parameter-level detail beyond what the schema already provides, so it fails to compensate for the low coverage.
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 identifies it as returning the highest or lowest rows, with a helpful plain-language gloss ('which is the most/least X'). It distinguishes itself from siblings like dataset_search and dataset_stats, though it doesn't explicitly say it returns full rows.
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?
No guidance is provided on when to use this tool versus alternatives. There is no mention of alternatives or conditions that would select this tool over dataset_stats or dataset_search. The description only explains what it does, not when it's appropriate.
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 has a clear purpose: schema, provenance, exact matching, substring search, multi-value comparison, numeric stats, and top/bottom ranking. The only potential confusion is between dataset_row, dataset_search, and dataset_compare, but their differing match semantics (exact single value, contains, and multi-value ordering) are described clearly enough.
All tools share the dataset_ prefix, making the group immediately recognizable and predictable. However, the suffix mix of nouns (columns, provenance, row, stats) and verbs (compare, search) breaks the strict verb_noun convention, though this is a minor deviation given the strong prefix consistency.
Seven tools is ideal for a single-dataset query server—enough to cover exploration, retrieval, and analysis without redundancy. Each tool earns its place, and the count is comfortably within the well-scoped range.
The set covers the full read-only lifecycle of dataset exploration: schema discovery, provenance, exact filtering, search, comparison, statistical summaries, and ranking. There are no obvious dead ends or missing operations for the apparent domain of answering questions about the Perdiemo dataset.