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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the notes that it 'Stores nothing' and is 'Deterministic' largely reinforce what is structured. The description goes further, though, and discloses genuinely non-structured behavior: the failure contract (template_rejects_sample rather than returning a bad template), the no-model inference rules, and 'free, no payment or account required'.

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?

It is dense but front-loaded: the core action and mechanism come first, then inference rules, then return/behavior guarantees. Each sentence carries information (returns, failure mode, storage, determinism, cost) with little duplication, though the single-block length is heavy for a 5-parameter tool.

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?

With no output schema, the description carries the burden of explaining returns and does so ('inferred', 'uncertain', 'listing_patch'), plus the failure mode and stateless/deterministic guarantees. It stops short of explaining what the agent should do with the `listing_patch` or how it relates to prepare_verification/get_template, leaving a small next-step gap.

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 description coverage is 100%, so 3 is the baseline. The description adds real meaning beyond the schema for `samples` ('more varied samples teach it which fields are optional') and explains how input drives inference and the bounds/rule derivation, which the schema alone does not convey.

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 states a specific verb and resource ('Builds a verification template ... from one to ten sample outputs') and discloses the mechanism ('a fixed procedure (no model)'), so the agent knows exactly what the tool produces. It does not explicitly differentiate itself from the sibling get_template or prepare_verification, which keeps it short of a 5.

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?

Usage is implied rather than stated: the agent must infer that this is the tool to call when it has sample outputs and needs a template built. There is no explicit 'use this instead of X' or when-not guidance against get_template/prepare_verification, and no prerequisites beyond 'one to ten samples'.

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