dataset_provenanceThe source, the date it was computed, the licence and the citation for the Csatzo 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?
No annotations are provided, so the description carries the full disclosure burden. It communicates that the tool returns provenance-related information and implies a read-only operation, but it does not explicitly state side-effect-free behavior or explain what the response format will look like.
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 concise sentences convey the content, purpose, and intended use without repetition or filler. The key information is front-loaded.
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 provenance metadata tool, the description is sufficiently complete: it lists the key information fields and explains the practical use. The lack of an output schema is not a major gap here since the field list is already stated.
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 parameter semantics are not a concern. The description does not need to compensate for any schema gaps, and the baseline of 4 applies.
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 resource as provenance metadata for the Csatzo dataset and enumerates the specific attributes (source, computed date, licence, citation). It lacks an explicit verb like 'get' or 'retrieve,' but the intent is unambiguous and distinct from the sibling tools.
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 clear use case: 'Read this to attribute a figure correctly.' It does not explicitly contrast with sibling tools, but the provenance-specific content makes the appropriate context evident.
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, and top each have a unique purpose. The row-returning tools (dataset_row, dataset_search, dataset_compare) could potentially be confused, but their exact-match, contains-search, and multi-value-ordering semantics are described clearly enough to prevent serious misselection.
All seven tools follow the predictable dataset_<operation> pattern, making the set easy to scan and understand. There is no mixing of naming conventions or styles.
Seven tools is a well-scoped size for a dataset exploration server. Each tool covers a distinct useful operation without redundancy or bloat.
The tool set covers the full read-only lifecycle of working with the Csatzo dataset: schema discovery, provenance, exact lookup, free-text search, comparisons, summary statistics, and top/bottom rows. No obvious missing operation would prevent an agent from answering typical questions about the data.