Estimate a domain's financial value from TLD tier, character length, commercial liquid floor, and enterprise upside to support informed pricing and investment decisions.
Calculates deep financial valuation model for a domain name based on TLD tier, character length, commercial liquid floor, and enterprise upside.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | The domain name to evaluate (e.g. cloudcompute.com) |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden, yet it discloses nothing about whether the valuation is deterministic or heuristic, what permissions or data sources are needed, or how the 'enterprise upside' factor is derived. 'Deep financial valuation model' implies sophistication but conveys no verifiable behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One dense sentence with the verb and the driving factors front-loaded; no filler and nothing to trim.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description should explain what the calculation returns (a dollar figure, a range, component scores), and it does not. Combined with absent annotations on a tool whose output drives financial decisions, the definition is materially incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the schema already documents the single 'domain' parameter with an example, so the baseline of 3 applies. The description explains what inputs feed the model (TLD tier, character length, liquid floor, enterprise upside) but those are derived properties of the domain, not additional parameter guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (calculates) and resource (financial valuation model for a domain name), plus the four factors driving the model. It does not differentiate itself from the sibling compare_sales_multipliers, which is the only missing element for a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No indication of when to use this versus compare_sales_multipliers, no prerequisites, and no exclusions. The agent must infer that valuation precedes comparison from the tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.