Hardware & Unit Economics

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

Annotations already declare readOnly/idempotent/non-destructive/no-open-world, so the safety profile is covered. The description adds real behavioral context beyond that: pure arithmetic, no I/O or external calls, results rounded to 2 decimals, and explicit error behavior for an unknown method or a missing method-required parameter. It also restates the return fields, which is redundant given the output schema, so it falls short of a 5.

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, method mapping, and constraints in a compact block. It loses a point for redundancy: the 'not for drug pipelines, use valuation_biotech' exclusion appears twice and the return-field enumeration duplicates the output schema.

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?

Given nine parameters, a 100%-covered schema, an output schema, and full annotations, the description covers everything an agent needs: method-dependent parameter selection, error semantics, determinism, rounding, and no-auth/no-rate-limit conditions. The output schema removes any need to explain return values in the description.

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 each parameter is individually documented, so the baseline is 3. The description goes beyond the schema by mapping which method requires which parameters (e.g., trl needs market_size + market_share + margin + multiple + trl_discount) and clarifying that non-selected parameters should be omitted with defaults applying. That conditional relationship is not expressed by the flat schema.

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/deep-tech valuation) and names the three concrete methods it computes (TRL-risk-adjusted valuation, gross margin, break-even volume), immediately distinguishing it from valuation_biotech. An agent can select it over the other valuation_* siblings without opening the 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?

Explicitly states when to use it (hardware/deep tech with technology-readiness risk) and names the alternative with its own condition (drug pipelines -> valuation_biotech). Nothing is left to inference, though the exclusion is stated twice.

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