dataset_provenanceThe source, the date it was computed, the licence and the citation for the Reputzo 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 provided, the description carries the full burden. It implies a safe read-only operation ('Read this') and lists what is returned. It does not explicitly state that there are no side effects or describe error behavior, but for a simple provenance lookup with zero parameters this is sufficient.
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?
Two short sentences, no filler, and the key information (what and why) is front-loaded. Every word earns its place, and the purpose is immediately clear.
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 zero-parameter, no-output-schema tool, the description fully covers what an agent needs: what the tool provides, for which dataset, and how to act on it. Nothing essential is missing.
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 the schema already shows. The baseline of 4 applies, and the description adds context about what the returned provenance data contains, which is more than expected.
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 states a specific resource (the Reputzo dataset's provenance) and lists the exact attributes it covers: source, computed date, licence, and citation. This clearly distinguishes it from sibling tools that handle columns, comparison, rows, search, stats, or top values.
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 states a concrete use case: 'Read this to attribute a figure correctly.' This tells the agent when to invoke it. It does not explicitly name alternative tools or exclusions, but the clear attribute-focus implies when it is relevant versus when other dataset tools would be better.
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 are clearly distinct (schema, provenance, stats, top), but dataset_row and dataset_compare can be confused since both filter by column values — the exact vs. multiple-values distinction is subtle, though search is clearly different with substring matching.
All tools follow the dataset_ prefix with a clear noun (columns, compare, provenance, row, search, stats, top), making the naming pattern perfectly consistent and predictable.
Seven tools is well-scoped for querying a single dataset, covering schema, content, search, comparison, statistics, ranking, and provenance without unnecessary bloat.
The surface covers all common dataset query operations (schema, lookup, filtering, search, stats, ordering, provenance), but there is no tool for aggregating by groups or listing dataset versions, which are minor gaps.