dataset_topThe highest (or lowest) rows of the Abutly 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 burden of behavioral disclosure. It only states the basic ranking behavior and does not mention edge cases such as non-numeric column values, missing data, tie handling, or whether full rows are returned.
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 short and front-loaded, carrying its core meaning in the first clause. The quoted phrase adds helpful intuition but is slightly redundant with the opening statement.
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 simple three-parameter tool, the description covers the main ranking concept but omits important calling context: the meaning of the limit parameter is left only to schema constraints, and there is no indication of return shape or behavior when the column is not numeric.
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%, so the description must compensate. It does clarify that 'column' must be numeric and implies the effect of 'ascending', but it leaves 'limit' without any real semantic guidance beyond the schema's min/max constraints.
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's function: returning the highest or lowest rows by a numeric column, framed as 'which is the most/least X.' This distinguishes it from broad dataset operations like search or stats, though it does not explicitly name sibling alternatives.
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: whenever an agent needs ranking by a numeric column. However, it offers no explicit guidance on when not to use it or which sibling tool might be more appropriate for similar needs.
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 clearly distinct role: schema inspection, provenance, exact lookup, substring search, multi-value comparison, numeric stats, and top/bottom ranking. Even though dataset_row and dataset_compare both retrieve rows by column value, their descriptions make the single-value vs multi-value distinction clear.
All tools share a consistent dataset_ prefix and use clear snake_case names. The suffixes are either nouns or verbs that accurately reflect the operation, making the naming predictable and easy to navigate.
Seven tools is well-scoped for a single-dataset query server. Each tool covers a distinct query need without redundancy or bloat.
The toolset covers the full range of dataset querying: schema inspection, provenance, exact match, substring search, multi-value comparison, numeric aggregation, and ranking. Since this is a read-only dataset server, no update/create/delete tools are needed.