Evidence and sources
get_evidenceOne product’s evidence entries, cited sources with check dates, unknowns and limitations, and the guide’s evidence review.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | A product id from a search result. |
get_evidenceOne product’s evidence entries, cited sources with check dates, unknowns and limitations, and the guide’s evidence review.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | A product id from a search result. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false, so the safety profile is covered. The description adds real value by enumerating the returned content, including check dates on sources and explicit unknowns/limitations — a transparency signal about data freshness and caveats that annotations cannot convey.
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?
A single dense clause with no filler, front-loading the scope ('one product's') before the content list. It is a sentence fragment rather than a full statement, which is acceptable but slightly clipped.
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?
With no output schema, the description must carry the return-value burden, and it does by enumerating the four content areas. What remains unclear is whether the response is paginated or how evidence entries are keyed, which for a single-parameter read tool is a minor gap.
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?
Only one parameter exists and schema coverage is 100%, with the pattern and the 'from a search result' provenance already documented in the schema. The description reinforces scoping to a single product but adds no format or sourcing detail beyond that, so the baseline 3 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 names the specific resource — one product's evidence entries, cited sources with check dates, unknowns/limitations, and the evidence review — which is clearly distinct content from get_product or compare_products. The verb is implicit ('get' from the name, 'one product's evidence entries' as the object), but an agent can still tell what it will receive.
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?
There is no statement of when to reach for this tool versus get_product, compare_products, or recommend_products, and no prerequisites or exclusions. Usage is only inferable from the noun phrase describing the payload.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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