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lusha-oss

Lusha MCP Server

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by lusha-oss

companyFilters

Retrieve available filter options for company prospecting, such as industries, sizes, and revenues. Explore filter values before building queries, with no credits charged.

Instructions

Get available filter options for company prospecting. No credits charged.

    FILTER TYPES:
    - names, industries, sizes, revenues, sics, naics, intentTopics
    - locations, technologies (require searchText parameter)
    
    Use to explore available filter values before building prospecting queries.
    
    Based on: https://docs.lusha.com/apis/openapi/company-filters

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filterTypeNoType of filter to retrievesizes
Behavior3/5

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

With no annotations, the description must disclose behavior. It states 'No credits charged' (positive behavioral trait) but omits read-only status, rate limits, or idempotency. The read-only nature is implied but not explicit, leaving some gaps for AI agents evaluating safety.

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?

Description is concise with clear front-loading: first sentence states purpose, then bullet list, then usage note, then source URL. Each part contributes meaning, though the searchText mention could be clarified.

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?

For a simple tool with one optional parameter, the description covers purpose and usage context. However, without an output schema, it lacks detail on the response structure (e.g., list of values, format). This leaves agents guessing the return shape, which is needed for proper invocation planning.

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?

The only parameter (filterType) is fully described in the schema (enum, default). The description adds value by listing filter types and noting that some require a searchText parameter. However, searchText is not in this tool's schema, causing potential confusion. Schema coverage is 100%, so baseline is 3; description adds marginal value but with inconsistency.

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?

Description clearly states the tool retrieves filter options for company prospecting, distinguishes from sibling tools (e.g., contactFilters) by specifying 'company prospecting', and explicitly lists filter types. The phrase 'Use to explore available filter values before building prospecting queries' further clarifies its role.

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

Usage Guidelines4/5

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

Description provides clear usage context: use before building prospecting queries. It notes that some filter types require a searchText parameter (even though that param isn't in the schema, hinting at broader context). Lacks explicit 'when not to use' or alternative references, but the guidance is sufficient for most scenarios.

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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