dataset_columnsThe columns, which of them are numeric, the row count and the provenance banner of the Reviewvo dataset. Call this first to learn the schema.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 must carry the behavioral burden. It discloses the specific information returned (columns, numeric flags, row count, provenance banner), which is helpful. However, it doesn't explicitly state that the tool is read-only or has no side effects, nor does it describe any other behavioral traits. This is a minor gap for a simple inspection tool.
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, well-structured sentence that front-loads the main purpose (columns, numeric flags, row count, provenance) and ends with a clear usage directive. Every word earns its place; there is no redundancy or 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?
Given the tool's simplicity (no parameters, no output schema), the description adequately explains what is returned and when to use it. It covers the essential information an agent needs to call it correctly. It could optionally mention that it is a read-only schema inspection, but that is not critical for invocation.
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 tool has zero parameters, so there is nothing for the description to explain beyond what is already evident. The baseline for 0 parameters is 4, and the description adds no confusion. It does not need to describe parameters since none exist.
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 purpose: to retrieve the columns, numeric flags, row count, and provenance banner of the Reviewvo dataset. It also includes a specific directive to 'Call this first to learn the schema,' which distinguishes it from siblings by establishing it as the entry point for understanding the dataset structure.
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 explicitly instructs to call this tool first, providing clear context for when it should be used. It doesn't name alternatives or exclusions, but the 'first' directive is a strong usage guideline that implies it precedes other dataset tools. This meets the 'clear context, no exclusions' benchmark.
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: schema, provenance, exact lookup, substring search, multi-value comparison, aggregate stats, and ranking. Minor overlap exists between dataset_row and dataset_compare (both match column values) and between dataset_columns and dataset_provenance (both expose provenance details), but the descriptions make the intended use clear.
All tools share the dataset_ prefix and use lowercase snake_case, giving a clear family identity. The suffixes mix nouns (columns, provenance, row, stats, top) with verbs (compare, search), which is a minor inconsistency, but the overall pattern is predictable.
Seven tools is well-scoped for a single-dataset querying server. Each tool has a distinct role and none feels redundant or unnecessary for the core task of exploring and analyzing the Reviewvo dataset.
The surface covers schema discovery, provenance, exact/string lookup, multi-value comparison, numeric summaries, and ranking, which covers the main ways an agent would explore a dataset. Minor gaps include no pagination for large result sets and no multi-column filter, but these are workable given the available tools.