prepare_consultation

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

The description adds a clear behavioral rule beyond annotations: the tool must not confirm on its own, and output is meant for user confirmation. This complements the readOnlyHint and idempotentHint annotations without contradicting them.

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?

The description is one compact sentence with two clauses; it front-loads the primary action and adds the confirm constraint with a semicolon. No filler words.

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 an output schema present and annotations declaring read-only, idempotent, non-destructive behavior, the description covers the essential flow: normalize, return settings, do not confirm. It lacks conditions on when to use it, but that is a usage-guideline gap, not a completeness gap for calling the tool.

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 0%, so the description must compensate. It labels the single payload parameter as 'consultation input,' which is more meaningful than the generic schema field, but it provides no structure or examples of expected payload fields.

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 action – normalizing consultation input – and identifies the deliverable (settings requiring user confirmation). It does not reference sibling tools like calculate_natal or search_knowledge, so differentiation is implicit rather than explicit.

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?

No guidance is given about when to call this tool versus siblings such as calculate_natal or save_run. The context that it is a preliminary step before confirmation is implied by the name and behavior, but never stated as a condition or alternative.

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