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linkedin-buying-signals

Get one prospect

get_prospect
Read-only

Everything known about one prospect: role, company, location, language, every detected signal with the verbatim quote from its source and the LinkedIn URL it came from, any existing email or LinkedIn draft, and outreach state.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
prospectIdNoThe prospect id from list_prospects
linkedinUrlNoTheir LinkedIn profile URL, if the id is unknown

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already establish readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds meaningful return-content context: it discloses that signals include verbatim quotes and LinkedIn source URLs, and that existing drafts and outreach state are included. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single dense sentence front-loads the core purpose ('Everything known about one prospect') and then lists concrete fields. Every clause adds information; there is no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description gives a strong inventory of returned fields, which is valuable given no output schema. However, it does not clarify how to choose between the two optional parameters, what happens if both or neither are provided, or any fallback behavior. For a simple lookup tool this is a noticeable gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents prospectId and linkedinUrl. The description does not add parameter-level guidance beyond indicating that the tool returns everything known about one prospect, which is enough to meet the baseline but not exceed it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear resource ('one prospect') and enumerates the specific data it returns: role, company, location, language, signals, verbatim quotes, source URLs, drafts, and outreach state. This distinguishes it from siblings like list_prospects and get_pipeline_stats by focusing on full detail for a single prospect.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied: this is for retrieving everything known about one prospect, while list_prospects is the obvious alternative for listing. However, the description never explicitly says when to use this tool versus alternatives, nor does it state that prospectId or linkedinUrl is the expected entry point.

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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