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Leviai-ai

publicfinance

by Leviai-ai

company_facts

Retrieve standardized financial facts like Revenue, NetIncome, and Assets from SEC EDGAR XBRL filings. Query by company ticker or CIK, with optional specific concept.

Instructions

Get XBRL financial data for a company from SEC EDGAR. Returns standardized financial facts like Revenue, NetIncome, Assets, etc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyYesCompany ticker symbol (e.g., AAPL) or CIK number
conceptNoSpecific XBRL concept to query (e.g., 'Revenue', 'NetIncomeLoss', 'Assets'). Use us-gaap taxonomy prefix for non-standard: 'us-gaap:AccountsPayableCurrent'. Without this, returns a summary of all available concepts.
Behavior3/5

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

With no annotations, the description covers return format (standardized financial facts) and mentions behavior when no concept is provided (returns summary). However, it lacks details on authentication, rate limits, or whether the operation is read-only.

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?

The description is a single sentence that efficiently conveys the primary action and output. It is front-loaded and concise, though it could benefit from a slightly more structured format (e.g., bullet points for parameters).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers basic functionality and key output examples but omits details like output format (single value vs. time series), pagination, or rate limits. Given no output schema or annotations, the description is adequate but leaves gaps for complex 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?

Both parameters have descriptions in the schema (100% coverage). The tool description adds value by explaining the 'concept' parameter's default behavior (returns summary if omitted), which goes 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 retrieves XBRL financial data from SEC EDGAR, specifying examples like Revenue, NetIncome, Assets. It distinguishes from siblings like 'company_filings' which likely deals with filings rather than standardized facts.

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

Usage Guidelines3/5

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

The description implies usage for obtaining financial facts from SEC filings but does not explicitly state when to use this tool versus alternatives like 'company_filings' or 'economic_overview'. No when-not-to-use guidance is provided.

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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