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TVLSS

HireJack

Find Companies

find_companies
Read-only

Segment companies by industry, role family, skill, hiring trend, and job-count range. Returns results sorted by total open jobs descending.

Instructions

Multi-axis company segmentation. Analyst tier. Filter by industry, role family they're hiring for, top-skill match, hiring trend, job-count range. Returns companies sorted by total open jobs descending. Use for 'fintech companies hiring ML engineers', 'defense tech companies scaling up', or 'who's hiring 100+ engineers and growing?'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax companies to return (default 25)
skillNoCompanies whose top skills include this (substring match)
trendNoHiring trend filter, from each company's 2-month rolling job-count average: 'up' = growing, 'down' = shrinking, 'stable' = flat.
familyNoCompanies hiring for this role family
maxJobsNoMaximum total open jobs (default unlimited)
minJobsNoMinimum total open jobs (default 0)
industryNoIndustry substring filter (case-insensitive). E.g. 'fintech', 'health', 'AI', 'defense'.
Behavior4/5

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

Annotations declare readOnlyHint true, and description adds sorting by total open jobs descending, consistent with read-only behavior.

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?

Two efficient sentences plus examples, all front-loaded with no redundant information.

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

Completeness4/5

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

Covers all key aspects of tool behavior and usage, though could mention pagination or data freshness more explicitly.

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 provides 100% coverage of parameter descriptions; description adds context but does not significantly supplement parameter details.

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?

Clearly defines the tool as multi-axis company segmentation with specific filters and sorting, distinguishing it from simpler search tools.

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?

Provides concrete examples of queries like 'fintech companies hiring ML engineers', but does not explicitly exclude cases or mention 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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