dataset_columnsThe columns, which of them are numeric, the row count and the provenance banner of the Take-Home Compass 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?
No annotations are provided, so the description carries the burden. It describes what information is returned but does not explicitly state that the operation is read-only or has no side effects, though the nature of returning schema metadata strongly implies it.
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 brief, direct, and front-loads the key purpose. Every sentence adds value, with no redundant or vague phrasing.
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?
The description conveys the main output elements (columns, numeric indicators, row count, provenance banner) and the intended first-step usage. It is complete enough for a simple schema-introspection tool, though it does not specify the exact output format.
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 and the schema coverage is 100%, so there is nothing missing. The description fully aligns with the empty parameter 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 clearly states that the tool returns columns, numeric flags, row count, and provenance banner for the Take-Home Compass dataset. It is distinct from sibling tools like dataset_compare or dataset_search by focusing on schema information.
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?
Explicitly advises 'Call this first to learn the schema,' giving clear situational guidance. It does not name alternative tools, but the instruction to call it first is actionable and sufficient for basic usage.
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 has a clearly distinct purpose: schema, provenance, exact-row lookup, substring search, multi-value comparison, aggregate stats, top/bottom ranking, and enquiry lifecycle steps. Even the three query tools (dataset_row, dataset_compare, dataset_search) are semantically separate and described with enough precision to avoid misselection.
All tools follow a consistent snake_case pattern with a domain prefix: dataset_* for the data exploration tools and enquiry_* for the form workflow. The suffix is sometimes a noun (columns, provenance, fields) and sometimes a verb (search, compare, submit), but the uniform prefix and predictable structure make the set easy to navigate.
Ten tools is a well-scoped size for a server covering two related areas: dataset analysis and enquiry submission. Each tool earns its place; there is no obvious redundancy or bloat, and the split of seven dataset tools and three enquiry tools matches the apparent purpose.
The dataset tools cover schema discovery, provenance, filtering, searching, comparison, statistics, and ordering—a solid analytical surface. The only notable gap is a way to retrieve all rows at once without a filter, though that may be intentionally omitted since most queries are targeted. The enquiry tools form a complete describe-fields-submit flow.