search_people
Prepare a paid PDL SQL person-search request. Exactly one profile is returned by the API.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| sql | Yes |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Prepare a paid PDL SQL person-search request. Exactly one profile is returned by the API.
| Name | Required | Description | Default |
|---|---|---|---|
| sql | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral disclosure. It does disclose that the request is paid and that exactly one profile is returned, which are useful operational facts. However, it leaves ambiguity about whether the tool actually executes the search or only prepares the request, and it does not mention error behavior, invalid SQL, or rate limits.
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 just two sentences with no filler, and each sentence carries useful information: the request's nature and the single-profile result. The phrasing 'Prepare a paid PDL SQL person-search request' is slightly awkward but still compact and 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 one-parameter tool with an output schema, the main missing pieces are parameter semantics and execution behavior. An agent still does not know how to construct a valid PDL SQL query or whether invoking the tool immediately triggers a paid call, so the description is not fully sufficient for correct invocation.
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?
Schema coverage is 0%, so the description must compensate for the undocumented 'sql' parameter. It adds that the SQL is PDL SQL and person-focused, but it does not explain the expected query grammar, required fields, or constraints, leaving the agent with only a partial understanding of the parameter.
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 identifies a person-search request and notes that exactly one profile is returned, so an agent can tell it targets people rather than companies. It does not clearly differentiate from person-focused siblings like enrich_person, find_lead, or find_decision_maker, and 'prepare a request' is an indirect way to describe the action.
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 guidance on when to use search_people versus alternatives such as enrich_person or search_companies. The description provides no conditions, exclusions, or context that would help an agent decide between sibling 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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