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Get Company Concept

get_company_concept
Read-onlyIdempotent

Get a specific financial metric for a company across all filings. Use this to track revenue, net income, or any XBRL tag over time. Example: get_company_concept(cik: "320193", taxonomy: "us-gaap", tag: "Revenue").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cikYesSEC Central Index Key (e.g., "320193" for Apple)
tagYesXBRL concept tag (e.g., "Revenue", "NetIncomeLoss", "Assets", "EarningsPerShareBasic")
taxonomyYesXBRL taxonomy: "us-gaap", "ifrs-full", "dei", or "srt"

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
cikYesSEC Central Index Key as numeric value
tagYesXBRL concept tag requested
labelYesHuman-readable label for the concept
unitsYesFinancial data grouped by unit (USD, shares, etc)
taxonomyYesXBRL taxonomy name
descriptionYesDetailed description of the concept
entity_nameYesLegal name of the company

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, etc. The description adds that data comes from 'across all filings', which is useful context not in annotations.

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 sentences and an example with no fluff. Every word adds value.

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 the output schema exists and annotations cover safety, the description is complete enough. No missing context for effective use.

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 coverage is 100% with good descriptions for each parameter. The description provides an example with real values, helping the agent understand parameter usage beyond the schema.

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 the tool gets a specific financial metric for a company across all filings, with a concrete example. It distinguishes from siblings like get_company_facts and get_company_financials by focusing on a single concept tag.

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 says to use this to track metrics like revenue or net income over time. While it doesn't mention when not to use it, the example and context provide clear guidance.

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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