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

Annotations already declare readOnly/idempotent/non-destructive/openWorld=false, but the description goes well beyond them: pure arithmetic with no I/O or external calls, results rounded to 2 decimals, decimals-not-percent convention, method-dependent defaults, and the fact that parameters belonging to other methods are accepted and ignored. This is exactly the extra context annotations cannot carry.

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?

Dense but front-loaded: the asset scope comes first, then routing, then per-method parameter lists, then conventions and error behavior. Every sentence carries information, though the run-on per-method parameter enumeration is heavy and could be more scannable.

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 14-parameter, method-dispatch tool with one required field, the description supplies everything an agent needs: method selection, required inputs per branch, defaults/ignored-parameter behavior, unit conventions, and error semantics. An output schema exists, so return-value detail is not needed.

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%, yet the description adds the crucial cross-parameter structure: which parameters each method requires (e.g. customer_relationships needs customer_count + avg_revenue_per_customer + retention_rate + profit_margin + discount_rate + projection_period), the [0,1] bounds on retention_rate/enforcement_probability, and the meaning of projection_period as the number of discounted periods. That grouping is not derivable from 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?

The description names the exact asset family (customer-related intangibles) and the three concrete formulas it supports (customer relationships, distribution networks, non-compete), with a specific verb (valuation via method selection). It explicitly routes the workforce and technology cases to valuation_human_capital and valuation_technology, so an agent can separate it from siblings without opening any 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 is given ('Use for customer relationships, distribution networks, and non-compete assets') plus named alternatives for the adjacent domains ('for workforce and key-person assets use valuation_human_capital; for technology assets use valuation_technology'). The default behavior and the failure condition (unknown method or missing method-required parameter returns an error) are also stated.

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