dataset_columnsThe columns, which of them are numeric, the row count and the provenance banner of the HeadcountDesk 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 behavioral burden. It discloses what the tool returns (columns, numeric indicators, row count, provenance banner) but does not explicitly state that it is read-only or side-effect-free. For a zero-parameter schema-introspection tool, the risk is low, but the lack of explicit safety language keeps it at a 3.
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 focused sentence that front-loads the output contents and ends with actionable usage guidance. Every phrase earns its place with 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?
Given the tool's simplicity, zero parameters, and clear enumeration of returned values, the description is nearly complete for correct invocation. A small gap remains: it does not state the response format or explicitly confirm the operation is read-only, but these are minor for this tool type.
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 are no parameter semantics for the description to clarify. The description appropriately focuses on what the output contains rather than inputs.
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 identifies the tool's resource (HeadcountDesk dataset) and contents (columns, numeric flags, row count, provenance banner), and frames it as the first call to learn the schema. It is distinguishable from sibling tools like dataset_row or dataset_stats, though it lacks an explicit verb like 'returns'.
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 instruction 'Call this first to learn the schema' gives clear sequencing guidance for the agent. It does not explicitly list when not to use this tool or name alternatives, but given the sibling list, the usage context is reasonably clear.
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 maps to a distinct query type: schema discovery, provenance, exact matches, substring search, value comparison, numeric stats, and top/bottom rows. The potential overlap between dataset_row and dataset_compare is mitigated by the explicit X-vs-Y ordering purpose of compare.
All tools share the consistent dataset_ prefix and snake_case, making the family immediately recognizable. However, suffixes mix nouns (columns, row, stats) with verbs (compare, search), so the pattern is not perfectly uniform.
Seven tools is a well-scoped set for interacting with a single read-only dataset. Each tool covers a distinct user need without redundancy or overwhelming breadth.
The dataset surface is complete for the apparent purpose: schema, provenance, exact lookup, full-text search, comparison, summary statistics, and ranked extremes are all available. No obvious query type relevant to this domain is missing.