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

With no annotations, the description carries the full burden, and it discloses little: 'industry-standard multiples' is vague about which multiples or formula are applied, and it never says whether the result is a single number, a range, or whether the call has any side effects. It does at least convey the calculation method's basis, which is some 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler, though it is arguably too terse given the gaps in usage and behavior disclosure.

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?

For a three-parameter pure calculation with no annotations and no output schema, the description covers the basic mechanics but omits what the return value looks like and how industry affects the result. Adequate but with clear gaps.

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%, so all three parameters, including the industry enum-like values, are already documented in the schema. The description adds only the idea that industry drives the multiple, which is a marginal restatement of the schema. Baseline 3 applies.

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?

The description names a specific verb (Calculates) and a specific resource (target acquisition value), plus the inputs that drive it (annual revenue/EBITDA, industry multiples). It is clear what the tool produces, though it never references or distinguishes itself from the sibling value_digital_asset.

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?

There is no statement of when to use this tool versus value_digital_asset, nor any prerequisites or exclusions. Usage can only be inferred from the phrase 'target acquisition value,' which is not enough to route between two valuation tools.

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

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.

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.

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.

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.

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.

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.