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BACH-AI-Tools

Li Data Scraper MCP Server

search_people

Find LinkedIn profiles by searching with filters, retrieving public data for professional networking and research purposes.

Instructions

You may see less than 10 results per page. This is because not all profiles as public, sometimes hiding profiles. The endpoint automatically filters these profiles from the result

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses a key behavioral trait: that results may be limited due to non-public profiles being filtered out. However, it lacks details on other aspects like rate limits, authentication needs, or error handling, making it only partially informative.

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

Conciseness3/5

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

The description is concise with two sentences, but it is not front-loaded with the tool's purpose. The first sentence addresses a limitation rather than the core function, which reduces clarity, though it avoids unnecessary verbosity.

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?

Given the tool's complexity (a search function with no parameters but behavioral nuances) and lack of annotations and output schema, the description is incomplete. It mentions result filtering but omits essential details like what the search criteria are, how results are returned, or error conditions, leaving significant gaps.

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

Parameters4/5

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

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description does not add parameter information, which is appropriate here, and it compensates by providing context about result filtering, aligning with the baseline for zero parameters.

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

Purpose2/5

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

The description fails to state what the tool actually does—it only describes a limitation of the results. It mentions 'search_people' in the tool name, but the description does not specify the action (e.g., searching for people by criteria) or the resource involved, making it vague and tautological by not elaborating beyond the name.

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 on when to use this tool versus alternatives. The description does not mention any context, prerequisites, or comparisons with sibling tools like 'get_public_profile_data_by_url' or 'get_profile_data_and_connection_u0026_follower_count', leaving the agent without usage direction.

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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