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

Annotations already cover read-only, idempotent, and closed-world, but the description adds substantial context beyond them: pure arithmetic with no I/O or external calls, 2-decimal rounding, no auth or rate limits, and the failure mode (unknown method or missing method-required parameter returns an error rather than a value).

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?

Front-loaded with purpose, routing, parameter mapping, and conventions in a compact block. The biotech exclusion is stated twice ('for drug pipelines use valuation_biotech' near the start and again as 'Not for drug pipelines'), which is mild redundancy in an otherwise tight description.

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 9-parameter, method-driven calculator with annotations and an output schema, everything needed to invoke correctly is present: routing, per-method parameter requirements, unit conventions, and error behavior. Return fields are named even though the output schema makes that optional.

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 the baseline would be 3, but the description goes further by mapping each method to its required parameter set (trl → market_size + market_share + margin + multiple + trl_discount, etc.) and stating that only method is required with the rest omitted. It also clarifies unit conventions (fractions as 0.10 = 10%, probability lists in [0,1] summing to 1), which the schema does not.

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+resource ('Hardware and deep-tech valuation') and enumerates the exact metrics produced (TRL-risk-adjusted valuation, gross margin, break-even volume). It explicitly distinguishes itself from the sibling valuation_biotech, so an agent can route without opening either schema.

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?

Explicit when-to-use ('hardware and deep tech with technology-readiness risk') and when-not ('for drug pipelines use valuation_biotech'), naming the alternative tool twice. It also explains that the method parameter selects the metric, which is the core routing decision.

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