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mcp-server-valuation

value_digital_asset

Calculate valuation for digital assets, domains, SaaS, brands, or content sites using liquid floors and enterprise multiples to estimate acquisition value.

Instructions

Calculates valuation models for digital assets, premium domains, and web properties based on liquid floors and enterprise multiples.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asset_nameYesName or identifier of the asset (e.g. cloudcompute.com, saas-tool)
asset_typeYesType: domain, saas, brand, or content_site

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
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 behavioral burden. It hints at methodology ("liquid floors and enterprise multiples") but says nothing about whether this is a read-only calculation, what permissions or inputs it requires, or what the result looks like — a significant gap for a valuation tool with zero annotation coverage.

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?

A single efficient sentence with the verb and resource front-loaded and no wasted words. It is well-sized, though the trailing methodology clause adds flavor rather than actionable detail.

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?

For a simple two-parameter calculator this is close to adequate, but with no output schema the description should at least indicate what is returned (a single value, a range, multiple model outputs). It also leaves the sibling relationship unresolved, so an agent cannot be fully confident it is choosing the right valuation tool.

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%, and both parameters (asset_name, asset_type) already carry examples and accepted types in the schema. The description adds no parameter-level detail, so the baseline 3 applies; the schema does the heavy lifting.

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 ("Calculates") and resource ("valuation models for digital assets, premium domains, and web properties"), which is more than a tautology. However, it never mentions or distinguishes itself from its sibling calc_ebitda_multiple, leaving the agent to guess which valuation tool applies to a given asset.

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 guidance, no prerequisites (e.g. asset must already have a liquid floor or EBITDA figure), and no mention of the sibling calc_ebitda_multiple as an alternative. The agent must infer usage entirely from the name.

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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