get_company
Get company facts (name, exchange, industry, regulator id, filings url).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Get company facts (name, exchange, industry, regulator id, filings url).
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It states what facts are retrieved, which is adequate for a simple lookup. However, it does not mention idempotency, rate limits, data freshness, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that communicates the tool's purpose efficiently. Every word adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, clear output, output schema exists), the description is mostly complete. It could mention the output schema or provide a usage example, but it is sufficient for basic understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should elaborate on the 'ticker' parameter. It only states 'ticker' in the schema title but adds no explanation (e.g., that it's a stock symbol). The description fails to add meaning beyond the parameter name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description contains a specific verb ('Get') and resource ('company facts'), and lists the exact fields returned: name, exchange, industry, regulator id, filings url. This clearly distinguishes it from sibling tools that focus on financial metrics or statements.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when basic company information is needed, but provides no explicit guidance on when to use this tool versus alternatives like get_financials or screen_companies. No when-not or prerequisite information is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct financial data aspect (e.g., balance sheet vs income statement vs cash flow; different holding types; metrics vs history). No overlapping purposes.
All tools follow verb_noun pattern with snake_case (e.g., get_balance_sheet, compare_metrics). Consistent and predictable.
19 tools is slightly above the typical 3-15 range but covers a broad domain (statements, metrics, holdings, screening). Still reasonable and well-scoped.
Covers most key financial data needs: statements, metrics, insider trades, institutional holdings, screen/search. Minor gaps like earnings estimates or dividend history are absent but core workflows are complete.