OpeningsFirst

Top companies

top_companies

Read-only

Which companies are hiring most for a search (same filters as search_jobs).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "top_companies"
  }
}

Input Schema

Name	Required	Description
`sort`	No
`limit`	No	Companies to list, default 20.
`query`	No	Any words: a job title, skill or kind of work ('LLM evaluation', 'SAP FICO', 'ICU nurse'). Matched on titles, skills and meaning.
`roles`	No	Role names from list_filter_options (e.g. 'Data Scientist'); other names are searched as words.
`cities`	No	Cities; means jobs in these cities (remote jobs elsewhere only if work_modes includes 'remote').
`levels`	No	Any of Intern, Entry level, Mid level, Senior, Lead / Manager, Director, Executive. Jobs whose level is not known are left out.
`yc_only`	No	Only Y Combinator startups.
`companies`	No	Only these companies (part of the name is enough).
`countries`	No	Countries, e.g. ['India'] or ['United States'].
`job_types`	No	Any of full_time, part_time, contract, temporary, internship.
`years_max`	No	Most years of experience.
`years_min`	No	Least years of experience the job asks for.
`skills_all`	No	Every one of these skills (e.g. ['go', 'kafka']).
`skills_any`	No	At least one of these skills.
`work_modes`	No	Any of remote, hybrid, onsite.
`skills_none`	No	None of these skills.
`posted_since`	No	Found by us since this date/time (ISO), e.g. 2026-10-20T08:00:00Z.
`years_strict`	No	True: leave out jobs that don't state years. Default false.
`hiring_systems`	No	Only jobs on these hiring systems (e.g. ['workday', 'greenhouse']); see list_filter_options.
`title_words_all`	No	Words that must all be in the title.
`title_words_none`	No	Words that must not be in the title (e.g. ['senior', 'lead']).
`exclude_companies`	No	Leave out these companies.
`include_recruiters`	No	Also recruiter, job-site and gig listings (default false: direct employers).
`key_employers_only`	No	Only well-known employers on our key lists.
`posted_within_days`	No	Posted in the last N days (1-90).

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 1, 2026

TDQS

B3.4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds that results are scoped to the same filter semantics as search_jobs, which is useful. It does not disclose the return shape (do companies come with counts? how are they ranked given the 'sort' enum?) despite there being no output 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?

A single sentence with no filler, and the key concept (ranking companies) is front-loaded ahead of the filter note. It is efficient, though the parenthetical is doing a lot of unstated work.

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 25-parameter, zero-required aggregation tool with no output schema, the description covers how to filter but not what comes back: company identity, ordering, counts, or typical result size are all unstated. Reliance on search_jobs as the filter reference is helpful but leaves the return contract entirely implicit.

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?

Schema description coverage is 96%, so the 25 parameters are already well documented in the schema itself. The description's one contribution is pointing at search_jobs as the reference for filter semantics, which aids wrap-around understanding but does not add per-parameter meaning. Baseline 3 applies.

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?

States a specific resource and framing: companies hiring most for a search. An agent can tell this is an aggregation over job postings rather than a job list, which separates it from search_jobs. It stops short of naming the sibling it differs from (company_jobs), but the verb+resource is unambiguous.

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?

"Same filters as search_jobs" gives real, actionable guidance for how to populate the 25 parameters, and the phrase "hiring most" implies this is the choice when you want ranked employers rather than individual postings. However, there is no explicit when-to-use/when-not statement and no mention of company_jobs or similar_jobs as alternatives.

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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