dataset_columnsThe columns, which of them are numeric, the row count and the provenance banner of the Longtailo 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?
Without annotations, the description carries the full burden of disclosing behavior. It lists the returned information (columns, numeric flags, row count, provenance banner) and implies a read-only inspection, but it does not explicitly state that the tool has no side effects. This is a minor omission but not misleading.
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, succinct sentence that conveys all necessary information without redundancy. It is well-structured for quick comprehension.
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 that this is a schema-inspection tool with no parameters, the description provides all necessary context: what it returns, what dataset it applies to, and when to call it. No additional details are needed for an agent to use it correctly.
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 no parameters, and the description does not need to explain any parameter semantics. Since the schema confirms zero parameters, the description is perfectly adequate in this regard.
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 that the tool returns the columns, numeric flags, row count, and provenance banner of the Longtailo dataset. It also explicitly directs the agent to call this first to learn the schema, making the purpose unambiguous.
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 includes a direct usage instruction: 'Call this first to learn the schema.' This tells the agent exactly when to use this tool, which is sufficient given that it has no parameters.
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 query mode—schema, provenance, exact match, search, comparison, stats, and top-N—so there is little real ambiguity. The main possible confusion is between dataset_row and dataset_compare, since both filter by column values, but the descriptions clarify that compare is for ordered multi-value lookups while row handles single exact-value matches.
All tool names follow a consistent dataset_<noun> pattern with lowercase snake_case, making the family easy to recognize and predict. Though the names use nouns rather than verbs, the convention is uniform and clear.
Seven tools is a well-scoped set for querying and analyzing a single dataset. Each tool covers a distinct data-access need without redundancy or unnecessary bloat.
The surface covers schema discovery, provenance, exact and fuzzy lookup, multi-value comparisons, numeric stats, and top/bottom selection, which is comprehensive for typical dataset questions. A minor gap is the lack of categorical frequency counts or a way to retrieve all rows without a filter, but agents can work around those by combining existing tools.