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bhaktatejas922

unipile-linkedin-mcp

get_search_params

Look up valid IDs for LinkedIn search filters by parameter type, like locations or industries, with an optional query to narrow results.

Instructions

Get valid parameter IDs for search filters.

LinkedIn search filters require specific IDs (not names). Use this tool to look up the IDs for locations, industries, companies, etc.

Args: param_type: Parameter type (case-insensitive) - one of: Common parameters: - "LOCATION" - Geographic locations - "INDUSTRY" - Industry categories - "COMPANY" - Companies - "SCHOOL" - Educational institutions - "PEOPLE" - People - "CONNECTIONS" - Connections - "SERVICE" - Services - "JOB_FUNCTION" - Job functions - "JOB_TITLE" - Job titles - "EMPLOYMENT_TYPE" - Employment types - "SKILL" - Skills

    Sales Navigator specific:
    - "REGION" - Regions
    - "DEPARTMENT" - Departments
    - "PERSONA" - Personas

query: Optional search string to filter results (e.g., "San Francisco")

Returns: List of valid parameter IDs and names for the specified type

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
param_typeYes
queryNo
Behavior4/5

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

With no annotations provided, the description carries the full burden. It clearly indicates this is a read-only lookup operation that returns a list of IDs and names. It does not mention potential side effects, rate limits, or authentication requirements, but for a simple lookup tool, the transparency is adequate.

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?

The description is well-structured with a brief intro, a clear explanation, a bulleted list of parameter values, and a return description. It is concise yet comprehensive, with no redundant information. Every sentence adds value.

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

Completeness5/5

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

Given the tool's simplicity and the absence of complex inputs/outputs, the description is complete. It explains the purpose, parameters, and return value adequately. No output schema is needed as the return description suffices.

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

Parameters5/5

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

Despite the input schema having no descriptions (0% coverage), the tool description provides exhaustive documentation for both parameters: it lists all possible values for param_type (categorized) and explains the optional query parameter with an example. This greatly exceeds the schema and adds crucial meaning.

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 clearly states the tool's purpose: 'Get valid parameter IDs for search filters.' It explains that LinkedIn search filters require IDs, and this tool looks up those IDs. This distinguishes it from sibling tools like search_people or search_companies, which perform actual searches rather than providing lookup IDs.

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?

The description explains the tool's use case: to look up IDs for locations, industries, companies, etc., for search filters. However, it does not explicitly state when not to use the tool or mention alternative tools. The usage context is implied but not fully spelled out.

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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