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jhgaylor

cleanjobdata-mcp

by jhgaylor

search_companies

Search for companies by name, website domain, or employer ID. Filter to active job listings and paginate results from the CleanJobData API.

Instructions

Search for companies using the CleanJobData API

query, website_url, and employer_id are mutually exclusive lookup modes, checked in priority order: employer_id, then website_url, then query.

Args: query: Company name to search for (fuzzy match, ranked by relevance) website_url: Match by registrable domain; accepts a bare domain or full URL employer_id: Look up one or more companies directly by ID (max 100) active: Only return companies with active jobs (default true) limit: Results per request (max 100 when searching) offset: Skip this many rows

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNo
activeNo
offsetNo
employer_idNo
website_urlNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations provided, the description takes full responsibility for behavioral disclosure. It reveals fuzzy matching, relevance-ranked results, a default for active (true), limits, and offset behavior, offering rich insight beyond the raw schema.

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 well-structured with a summary line and an Args list, and every sentence adds valuable detail. It is slightly verbose due to explaining mode interactions, but this is necessary for correct tool usage.

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 an output schema exists, return format details are unnecessary. The description covers all six parameters, mode priority, defaults, constraints, and search behavior, making it complete for an agent to select and invoke the tool correctly.

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?

The input schema has no parameter descriptions (0% coverage), but the description's Args section thoroughly explains every parameter, including mutual exclusivity, accepted formats, defaults, and max values, fully compensating for the schema's silence.

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 'Search for companies using the CleanJobData API' and enumerates three distinct lookup modes (query, website_url, employer_id), making the tool's purpose specific and distinguishable from job-focused siblings.

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?

It explicitly explains that query, website_url, and employer_id are mutually exclusive and checked in priority order, providing clear guidance on when to use each mode. However, it does not directly compare this tool with sibling tools like get_company or search_jobs.

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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