dataset_statscount, min, max, mean, median and sum of a numeric column of the Sopvo 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 burden of behavioral transparency. It usefully discloses that grouping commas and currency are handled and that non-numeric rows are excluded and counted, but it does not mention behavior for empty columns, missing columns, or error cases.
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 clear sentence with no redundant information or filler. It efficiently conveys the tool's purpose and key handling behavior.
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?
Given there is no output schema, the description adequately lists the returned statistics and mentions non-numeric row handling. It could be more complete by describing the exact output structure, but it is sufficient for a simple stats tool.
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 input schema only states that 'column' is a required string. The description adds that the column must be numeric, which is helpful, but it does not clarify allowed column names, whether the column must exist, or other format expectations.
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 title and description clearly state that the tool computes summary statistics for a numeric column in the Sopvo dataset, listing the exact statistics (count, min, max, mean, median, sum). This distinguishes it from sibling tools like 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 description explains what the tool does but provides no guidance on when to choose it over sibling tools, nor does it mention alternatives or the conditions under which it should be preferred.
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 targets a distinct operation on the Sopvo dataset: schema (columns), metadata (provenance), exact row retrieval (row), substring search (search), statistics (stats), ranking (top), and value comparison (compare). No two tools overlap in purpose, making selection unambiguous.
All tools follow a consistent 'dataset_<operation>' pattern with lowercase snake_case, such as dataset_columns, dataset_search, and dataset_stats. The naming is uniform and predictable, aiding agent selection.
With 7 tools, the server is well-scoped for exploring a single dataset. Each tool covers a necessary aspect—schema, provenance, data access, search, stats, and top/bottom queries—without bloat or missing essentials.
The tool surface comprehensively covers the domain of dataset exploration: schema discovery, metadata, exact and fuzzy retrieval, comparison, statistical summaries, and extreme-value queries. No obvious gaps exist for a read-only dataset server.