dataset_provenanceThe source, the date it was computed, the licence and the citation for the MultiplesBook dataset. Read this to attribute a figure correctly.
| 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 carries the full burden. It discloses the content returned (source, date, licence, citation) but does not specify the output format (e.g., plain text vs JSON) or any caveats like versioning or licensing nuances. This is a moderate gap for a metadata 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 two sentences, front-loading the key details (source, date, licence, citation) and immediately stating the use case. No wasted words; every sentence earns its place.
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?
For a simple, parameterless metadata tool, the description adequately lists what will be returned. While it omits output format details, the lack of an output schema is not a major issue given the tool's simplicity. It is complete enough for an agent to call 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 zero parameters and an empty schema, so the description need not explain parameter semantics. The baseline for 0-parameter tools is 4, and the description appropriately focuses on the returned information rather than input requirements.
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 returns provenance information (source, computation date, licence, citation) for the MultiplesBook dataset. This is specific and distinct from sibling tools that handle columns, comparisons, rows, search, stats, and top values, 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 tells the agent to use this tool when needing to attribute a figure correctly, which provides clear usage context. It doesn't explicitly name alternatives or exclusions, but the distinction from siblings is implied by the metadata-focused content.
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.
Most tools target distinct query types: schema, provenance, exact row lookup, search, comparisons, stats, and top/bottom. However, dataset_row, dataset_search, and dataset_compare have some functional overlap around filtering rows, which could lead to selection mistakes.
All tools follow a consistent dataset_<operation> pattern with clear nouns describing the operation. This makes the tool set predictable and easy to navigate.
Seven tools is well-scoped for a single-dataset query server. Each tool covers a distinct common question type without unnecessary proliferation.
The surface covers the main ways users would query the dataset: schema, exact matches, substring search, comparisons, stats, and top/bottom. A minor gap is the lack of a simple 'get all rows' or pagination tool, but that is not required for the apparent Q&A purpose.