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xpay✦ Finance Collection

getLeveredDCFValuation

Analyze a company’s value with the FMP Levered Discounted Cash Flow (DCF) API, which incorporates the impact of debt. This API provides post-debt company valuation, offering investors a more accurate measure of a company's true worth by accounting for its debt obligations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesStock symbol

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. First observed

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the full burden for behavioral disclosure. It explains the tool's core purpose (post-debt valuation) but does not mention return format, data availability, or any limitations. As a read-only tool, the lack of explicit safety disclosure is less critical, but the description could provide more detail about what the agent should expect.

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?

The description is two sentences, front-loaded with the main action ('Analyze a company's value'), and every sentence contributes meaningful context about the tool's purpose. No fluff or redundancy.

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 relatively simple (one parameter, no output schema), but the description leaves out details about the response structure or any assumptions used in the DCF. Without an output schema, the description could better indicate what fields or valuation data the agent will receive, making it only minimally complete.

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% (only 'symbol' with description 'Stock symbol'), so the schema fully documents the parameter. The description reuses the concept of a company but adds no additional detail about the parameter beyond what the schema already provides, meeting the baseline expectation.

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 analyzes a company's value using the FMP Levered DCF API, explicitly mentioning it incorporates debt impact and provides post-debt valuation. This distinguishes it from unlevered DCF tools like getDCFValuation.

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?

The description provides clear context that this tool is for levered DCF valuation accounting for debt, implying when to use it. However, it does not explicitly mention alternatives or when not to use it, so it stops short of the explicit guidance required for a 5.

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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