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Edgar — SEC Company Financials for AI Agents

get_company

Read-onlyIdempotent

Returns one company's EDGAR profile by ticker or CIK — name, exchange, industry (SIC), fiscal year end, entity type, and state of incorporation — plus whether standardized financials are loaded for it and, if so, how many facts and the latest reported period. Use after search_companies to confirm a company's identity and financials availability; use get_financials instead for the statements themselves. Read-only; no API key. Provide ticker or cik; if both are given, cik takes precedence. Any listed ticker for a company resolves to that company, not just its primary ticker.

Input Schema

NameRequiredDescriptionDefault
cikNoSEC CIK number, e.g. 1045810 (takes precedence over ticker)
tickerNoTicker symbol, e.g. 'NVDA' (any ticker the company lists)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / cik / description
      Previous value: -"SEC CIK number, e.g. 1045810"New value: +"SEC CIK number, e.g. 1045810 (takes precedence over ticker)"
    • changedInput schema / properties / ticker / description
      Previous value: -"Ticker symbol, e.g. 'NVDA'"New value: +"Ticker symbol, e.g. 'NVDA' (any ticker the company lists)"
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive behavior, and the description usefully adds 'no API key', the cik-over-ticker precedence rule, and the non-obvious fact that any listed ticker resolves to the company. It stops short of return format or rate-limit details, so not a 5.

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?

Tightly front-loaded: what it returns comes first, then usage routing, then invocation rules. The single long field-list sentence is dense but every clause carries information; only slight trim opportunity.

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?

Output schema is absent, but the description enumerates the return fields and the financials-availability payload, so the agent knows what comes back. For a two-parameter read tool with full annotation coverage, nothing essential is missing.

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 coverage is 100% and the schema already documents both parameters, including that cik takes precedence and that any listed ticker works. The description restates these rules rather than adding new semantics, which is the baseline-3 case.

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?

States a specific verb and resource ('Returns one company's EDGAR profile') and enumerates the returned fields, so an agent knows exactly what it gets. It also explicitly distinguishes itself from get_financials, which returns the statements themselves.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit placement in a workflow ('Use after search_companies to confirm identity and financials availability') and names the alternative with its selecting condition ('use get_financials instead for the statements themselves'). No inference required.

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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