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

Going beyond the annotations, it discloses that the tool is pure arithmetic with no I/O or external calls, rounds to 2 decimals, requires no auth and has no rate limits, and returns an error (not a value) on an unknown method or missing required parameter. It also specifies fraction conventions for rates and [0,1]-with-sum-to-1 for probability/weight lists.

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, then usage, then the method-to-parameter mapping, then return/behavioral notes — a logical flow with no filler sentences. It is dense and somewhat long, but each sentence carries distinct information, so the length is justified by the ten-method surface.

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 33 parameters, one required field, an output schema, and full annotations, the description supplies everything the schema cannot: method routing, precondition against siblings, unit conventions, error behavior, and precision. Nothing an agent needs to invoke a specific method correctly is missing.

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 already 100%, but the description adds real cross-parameter meaning that no single field description conveys: which parameters each method requires, that only `method` is required, and that unneeded parameters should be omitted with defaults applying. It does not restate the numeric meaning of individual fields, which the schema already handles.

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?

Opens with a specific verb and resource ('Allocate value across stakeholders and equity classes') and enumerates the ten supported allocation methods, so the agent knows exactly which class of task this covers. It also explicitly separates itself from the company-value siblings by stating it splits an already-known value across the cap table.

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?

Gives an explicit precondition ('Use only after the company-level value is known (from valuation_core, valuation_saas, or valuation_comparables)') and an explicit exclusion ('for the company value itself do not use this tool'). It also routes per-method parameter requirements, so the agent knows which fields to supply for each branch.

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