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Resolve a company identifier

find_company
Read-onlyIdempotent

Resolve any company identifier to its EDGAR identity: ticker in any format (AAPL, NASDAQ:AAPL, $NVDA, BRK.B), company name, CIK number, US ISIN, or CUSIP. Returns ranked candidates with name, ticker, and CIK. Use it when unsure of the exact ticker before calling the search tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe identifier to resolve, e.g. "nvidia", "NASDAQ:AAPL", "1045810", "US0378331005".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / $schema
      Added value: +"https://json-schema.org/draft/2020-12/schema"
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint and idempotentHint, so safety is covered. The description adds value by explaining the output behavior: it returns 'ranked candidates with name, ticker, and CIK,' which tells the agent to expect potential ambiguity and ranked resolution.

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?

The description is two sentences, front-loaded with the primary action and scope, and every sentence earns its place. The usage guidance is appended naturally without redundancy.

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?

With only one parameter, clear annotations, and no output schema, the description covers the essential context: what the tool does, what inputs it accepts, and what the return looks like. An agent has enough information to select and invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and the schema already gives examples, but the description adds meaningful context by listing the full range of accepted formats: ticker variants, company name, CIK, ISIN, and CUSIP. This helps the agent understand what kinds of strings are valid inputs.

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 names a specific verb ('Resolve'), a specific resource ('any company identifier to its EDGAR identity'), and enumerates the accepted input formats. This clearly distinguishes the tool from its siblings and leaves no doubt about its core function.

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 description explicitly tells the agent when to use the tool: 'when unsure of the exact ticker before calling the search tools.' It provides clear context and timing, though it does not name specific sibling tools or state when not to use it.

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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