dataset_topThe highest (or lowest) rows of the Rollupvo 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 carry the full burden of behavioral disclosure. It only states the core operation (rank rows) but does not mention output format, handling of ties, non-numeric columns, or any side effects. This is a significant gap for a tool with no annotation support.
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. It avoids redundancy with the title while adding the key detail of 'highest or lowest' and an illustrative example. It is efficient but could benefit from a bit more structure.
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 has no output schema, so the description must explain what the return value looks like. It only says 'rows' without detailing format or content. Additionally, with low schema coverage and no parameter explanations, the description is not complete enough for an agent to call the tool correctly without additional inference.
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 tool description adds a hint that 'column' must be numeric, but it does not explain the meaning or usage of 'limit' or 'column' beyond that. The description fails to compensate for the low schema 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 verb 'rank' (via 'highest/lowest rows') and the resource 'Rollupvo dataset by a numeric column', making the tool's function explicit. It differentiates from siblings like dataset_row or dataset_search by focusing on ranking rather than fetching or searching.
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 'which is the most/least X', giving clear context for when to use this tool. However, it does not explicitly mention alternatives or when not to use it, so it falls short of a 5.
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, search, and top-N are easy to separate. Dataset_row and dataset_compare both filter rows by column values, though dataset_compare is specifically for ordered multi-value comparisons and dataset_row is exact single-value lookup.
All tools share the consistent dataset_ prefix and snake_case style, making the set feel predictable. The second part mixes nouns and verbs slightly (columns, compare, row, search, stats, top), but the overall pattern is still coherent.
Seven tools is well-scoped for a single dataset exploration server. Each tool covers a distinct query need without redundancy or excessive granularity.
The server covers schema discovery, provenance, exact lookup, substring search, comparisons, numeric stats, and top/bottom ordering. Minor gaps like distinct-value enumeration or arbitrary sampling exist, but the core read-only exploration surface is well covered.