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Glama

get_company_concept

Read-onlyIdempotent

Fetches historical XBRL concept data like Revenues or Assets for a company ticker from SEC EDGAR, enabling financial trend analysis.

Instructions

Get specific financial concept data for a company.

Args: ticker: Stock ticker symbol concept: XBRL concept (e.g., 'Revenues', 'NetIncomeLoss', 'Assets')

Returns: Dictionary containing concept data over time

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYes
conceptYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is fully covered. The description adds that data is returned 'over time' (a time-series hint), but says nothing about rate limits, auth, or data sources beyond the annotations.

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?

Front-loaded with the core purpose followed by compact Args/Returns sections. The Args section largely restates the schema, which is minor waste, but overall it is tight and readable.

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 tool is a simple read-only lookup with a covered output schema and rich annotations, so little is required. Still, the missing sibling differentiation (get_xbrl_frames vs get_company_concept) leaves an agent without enough context to select correctly among near-identical tools.

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 description coverage is 0%, so the description must carry parameter meaning, and it does document both params: ticker as the stock symbol and concept as an XBRL concept with three concrete examples. That compensates partially, but format/casing expectations for ticker and valid concept names beyond the examples remain undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Get specific financial concept data for a company') and clarifies what a concept is with concrete XBRL examples. However, it does not distinguish itself from close siblings like get_xbrl_frames or get_company_facts, so an agent cannot route between them from the description alone.

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

Usage Guidelines2/5

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

No when-to-use, when-not-to-use, or alternative-tool guidance is given. With siblings like get_xbrl_frames and get_company_facts in scope, the agent gets no help deciding which tool to call.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.