person_enrichmentFind person data by email including name, position, company, and social profiles
| Name | Required | Description | Default |
|---|---|---|---|
| Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "$schema": "http://json-schema.org/draft-07/schema#",
+ "additionalProperties": false,
+ "properties": {
+ "data": {}
+ },
+ "required": [
+ "data"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, covering the main behavioral traits. The description adds the type of data returned, which is mildly useful, but does not discuss limitations, data freshness, or any other behavioral nuances beyond what annotations provide.
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 efficient sentence with no wasted words. The verb is front-loaded and the rest of the sentence adds specific, useful detail about the expected output.
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 one-parameter read-only lookup with an output schema and annotations, the description is mostly sufficient. However, it does not steer the agent away from overlapping sibling tools like email_enrichment or combined_enrichment, which is a notable gap in a list of nearly 40 tools.
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 input schema describes the email format via pattern/format but has no description for the parameter. The description only says 'by email', adding minimal semantic value about the parameter's role. With 0% schema description coverage, more compensation was 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 clearly states a specific action ('Find person data by email') and names the resource and key output fields (name, position, company, social profiles). It is distinct from company/domain tools, but does not explicitly differentiate itself from closely related siblings like email_enrichment or combined_enrichment.
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?
Usage is only implied: the agent can infer it should be used when it has an email and wants a person's details. There is no explicit when-to-use/when-not-to-use guidance or mention of alternatives, despite a large sibling list containing similar enrichment tools.
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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