get_prospect_research
A prospect's latest research (facts with sources) and personalised lines: icebreaker, connection note, LinkedIn message, email subject and body.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| prospect_id | Yes |
A prospect's latest research (facts with sources) and personalised lines: icebreaker, connection note, LinkedIn message, email subject and body.
| Name | Required | Description | Default |
|---|---|---|---|
| prospect_id | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description still adds real value by disclosing that only the LATEST research is returned and by enumerating the returned artefacts (facts with sources, icebreaker, connection note, LinkedIn message, email subject/body) in the absence of an output schema.
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 sentence with no padding; the most important element (what is returned) is front-loaded. It is slightly weakened by being a fragment without a verb, but nothing is wasted.
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 does the right thing by enumerating return contents, and the annotations cover safety. It stops short of clarifying the key ambiguity for this tool family: whether calling it returns cached research or triggers a new research run, which matters given the research_prospects sibling.
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 description coverage is 0% for the single required prospect_id, so the description must compensate. 'A prospect's...' implicitly establishes that prospect_id selects which prospect, but gives no format, source, or example of the identifier, leaving the schema and description jointly thin.
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 resource ('a prospect's latest research and personalised lines') and enumerates its contents, so an agent can infer this is a read of stored research. However, it is a noun fragment with no verb, and it gives no differentiation from the sibling research_prospects, which likely triggers generation rather than retrieval. Purpose is identifiable but not sharply distinguished.
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 when-to-use guidance, no prerequisites, and no mention of alternatives such as research_prospects or search_prospects. The agent must infer that this is the read path and research_prospects the write path entirely from the tool names.
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.