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xpay✦ Finance Collection

calculateCustomDCF

Run a tailored Discounted Cash Flow (DCF) analysis using the FMP Custom DCF Advanced API. With detailed inputs, this API allows users to fine-tune their assumptions and variables, offering a more personalized and precise valuation for a company.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. First observed

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only mentions it uses the FMP Custom DCF Advanced API and fine-tunes assumptions; it does not disclose output format, whether it returns a valuation estimate, any rate limits, or side effects. The description lacks substantive behavioral context.

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 concise at two sentences and front-loads the core action. The second sentence is somewhat generic and could be replaced with more specific information, but it is not overly verbose.

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

Completeness2/5

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

Despite having a nested input object with many optional parameters and no output schema, the description is minimal. It does not explain the expected return value, the required 'symbol' field, or provide enough context for an agent to know how to construct a valid request. The complexity is high, but description offers little support.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% in the tool description; the description does not mention any parameter names or meanings, just 'detailed inputs'. Even the input schema's descriptions are terse (e.g., 'Beta'), and the description fails to add any semantic context or clarify which parameters are required.

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?

The description clearly states the tool runs a tailored Discounted Cash Flow analysis, using a specific verb and resource. It distinguishes itself as 'custom' from standard DCF tools, but does not explicitly differentiate from the sibling tool calculateCustomLeveredDCF.

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 when a user needs fine-tuned, personalized valuation assumptions ('tailored', 'fine-tune assumptions'), but it provides no explicit when-to-use or alternative guidance. It does not mention scenarios where standard or levered DCF might be more appropriate.

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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