dataset_statscount, min, max, mean, median and sum of a numeric column of the Huddlevo 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 provided, the description carries the full burden of behavioral disclosure. It adds useful context: grouping commas and currency are handled, and non-numeric rows are excluded and counted. This goes beyond the title, though it could say more about empty-column or missing-value behavior.
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 one tightly written sentence that front-loads the list of statistics and places the caveats in parentheses. Every phrase adds information, and there is 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 single-parameter tool, the description covers the core statistics and important parsing/exclusion behavior. It does not specify the return format or mention sibling alternatives, but the tool is simple enough that these gaps are minor.
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?
The schema only defines 'column' as a non-empty string, so the description adds meaning by specifying it must be a numeric column of the Huddlevo dataset. This compensates well for the 0% schema description coverage, though it does not detail how column names should be referenced.
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 operation: it returns summary statistics for a numeric column of the Huddlevo dataset, explicitly listing count, min, max, mean, median, and sum. This makes it easy to distinguish from siblings like dataset_columns or dataset_row.
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 numeric summary statistics and notes handling of non-numeric rows, but it does not explicitly say when to prefer this over sibling tools or when not to use it. There is no mention of alternatives such as dataset_columns for discovering column names.
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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Most tools are clearly separated by query type: exact match, contains search, compare, stats, top, schema, and provenance. There is minor overlap between dataset_row and dataset_compare for simple equality lookups, but the descriptions make the intended use clear enough.
All tools share the dataset_ prefix and use snake_case, which creates a predictable family. However, the second part mixes nouns (columns, provenance, row, stats), verbs (compare, search), and adjectives (top), so it is not a strict verb_noun convention.
Seven tools is a well-scoped number for a single-dataset query interface. Each tool addresses a distinct common question type, and none feel redundant or excessive.
The set covers schema discovery, exact value lookup, substring search, multi-value comparison, numeric statistics, extreme values, and provenance. Minor gaps include no distinct-values tool and no paginated full-table retrieval beyond the 50-row search cap, but core exploration workflows are supported.