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List tracked companies

list_companies
Read-only

List companies in the benchmark catalog (customers, competitors, industry peers). Filter by name substring, industry, or tracking. Returns ids you pass to every other tool.

Input Schema

NameRequiredDescriptionDefault
limitNoMax rows, default 200, max 500.
queryNoCase-insensitive name substring, e.g. "rho".
industryNoExact industry label, e.g. "Sales & Marketing Tech", "AI Infrastructure", "Fintech". Omit to see all industries.
trackingOnlyNoOnly companies in the scheduled scrapes (tracking_enabled). Default false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / limit / description
      Previous value: -"Max rows, default 200."New value: +"Max rows, default 200, max 500."
  2. First observed

TDQS

A3.8/5.0
Behavior3/5

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

readOnlyHint=true already establishes a safe read, and the description adds genuinely useful context by saying the return is ids consumed by other tools. It does not add anything about default result volume (the 200 default lives only in the schema), pagination, or truncation behavior, so with annotations carrying the safety profile a 3 fits.

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?

Three short sentences, no filler, with the catalog scope stated first, the filter options second, and the downstream-consumption fact last. Every sentence earns its place.

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?

For a low-risk read-only list tool with full schema coverage and no output schema, the description covers what the tool is for and how its output is used downstream. It stops short of noting result-volume defaults or truncation, which an agent calling a list endpoint would want.

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 100%, so all four parameters including limit, query, industry, and trackingOnly are already documented with defaults and examples. The description only restates the filter dimensions the schema already names, adding example-free redundancy rather than new meaning.

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 verb and resource (list companies) and scopes the domain as the 'benchmark catalog' with concrete examples of what a company is (customers, competitors, industry peers). It does not explicitly distinguish itself from siblings like industry_landscape or category_breakdown, which keeps it just short of a 5.

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?

The clause 'Returns ids you pass to every other tool' tells the agent this is the entry-point lookup tool, and the filter list ('by name substring, industry, or tracking') names the ways to narrow it. There is no explicit when-not-to-use or named alternative, so it stops at 4.

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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