dataset_statscount, min, max, mean, median and sum of a numeric column of the Soapvo dataset (grouping commas and currency are handled; non-numeric rows are excluded and counted).
| Name | Required | Description | Default |
|---|---|---|---|
| column | Yes |
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 discloses parsing behavior (grouping commas and currency) and how non-numeric rows are handled (excluded and counted), which is valuable beyond the schema. It stops short of stating output shape or side effects explicitly, but the operation is read-only by nature.
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?
A single front-loaded sentence lists the exact statistics first and then packs useful parsing details into a parenthetical. No filler.
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 one-parameter aggregation tool with no output schema, the description covers the return stats and the important exclusion/formatting behaviors. It is sufficient for an agent to call the tool, though an explicit note about output shape would make it fully complete.
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 coverage is 0%, so the description must compensate. It adds meaning to the column parameter by specifying it must be a numeric column in the Soapvo dataset. It does not explicitly state that it is a required column name, though that is present in the schema.
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 identifies the operation (computing count, min, max, mean, median, sum) and the target (a numeric column of the Soapvo dataset), which is clear. However, it does not explicitly contrast itself with sibling tools such as dataset_top or dataset_search.
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 context for using this tool is implied: when summary statistics for a numeric column are needed. There are no explicit when-not-to-use conditions, prerequisites, or references to alternative sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool targets a distinct operation type (schema, provenance, exact lookup, substring search, multi-value compare, stats, top/bottom), so boundaries are mostly clear. dataset_compare is slightly vague by name but its description distinguishes it from dataset_row and dataset_search.
All tools follow a predictable `dataset_<topic>` snake_case pattern. Even though some suffixes are nouns and some are verbs, the uniform prefix and lowercase underscore style make the set feel consistent.
Seven tools is a well-scoped size for a single-dataset exploration server. Each tool serves a clear querying or metadata need without redundancy.
The toolkit covers schema, provenance, exact match, search, multi-value comparison, numeric stats, and top/bottom rows—a broad and practical surface. Obvious missing pieces are distinct-value enumeration and group-by aggregates, but most common questions can be answered with the existing tools.