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webanalyticsprobd-maker

LinkedIn Intelligence & Research MCP Server

linkedin_create_lead_shortlist

Generate a curated shortlist of top prospects matching your ideal customer profile, using filters like business type, decision-maker title, and target services.

Instructions

Generates a curated shortlist of top prospects (e.g. Top 20 PPC agency founders).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
icpNo
nameNoTop Prospects Shortlist
limitNo
Behavior2/5

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

There are no annotations, so the description carries full responsibility for behavioral disclosure. It only says 'Generates a curated shortlist' with no details about whether this is a search, a scoring operation, a destructive action, whether results are stored, or what side effects might occur. The behavior beyond the obvious output remains opaque.

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

Conciseness4/5

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

The description is a single sentence with no fluff and a concrete example. It is front-loaded with the core verb and resource. While more detail is needed elsewhere, the conciseness itself is effective.

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

Completeness2/5

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

This tool has a nested icp object with required fields, a default limit, and no output schema, yet the description provides almost no contextual information. An agent would not know how to construct a valid icp, what the output looks like, or how this tool fits into the broader lead-generation workflow. The description is too thin for the tool's complexity.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate, but it does not meaningfully explain the parameters. The example 'Top 20 PPC agency founders' hints at the limit and ICP concept, but it never explains the icp object, its required nested fields, or how limit behaves. The schema contains more detail than the description.

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

Purpose4/5

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

The description states a specific action ('Generates') and resource ('a curated shortlist of top prospects') with a concrete example. It is clear about what the tool accomplishes, but it does not distinguish itself from sibling tools like linkedin_rank_leads or linkedin_filter_leads, which could also produce shortlists.

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

Usage Guidelines2/5

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

No guidance is provided about when to use this tool versus alternatives. The description implies it is used to generate a shortlist, but it does not state prerequisites, exclusions, or how this differs from linkedin_find_opportunities, linkedin_rank_leads, or linkedin_filter_leads.

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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