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

Annotations only declare the generic mutation profile (readOnlyHint=false, idempotentHint=false); the description goes well beyond them by disclosing side effects (creates a project on the user's GoNoGo account), the non-idempotent one-interview-per-idea rule, and the interaction protocol (user taps Start and talks, the agent must stay silent while the interview runs). These are exactly the behavioral facts an agent cannot derive from structured fields.

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 paragraph is front-loaded with the decisive when-to-use clause and closes with exclusions and the interaction rule, so an agent can stop reading early. It is somewhat long and repeats the problem/payment theme across sentences, keeping it just short of maximally tight.

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, return values need no explanation, and the description still covers the important remainder: side effects (project creation), cardinality constraint, agent behavior during the interview, and the research/verdict that follows. Nothing needed to invoke or orchestrate this tool 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 description coverage is 100%, so both parameters (idea, language) are already documented with format constraints (maxLength 500, ISO 639-1 pattern). The description mentions the idea is in the user's words and implies the chat language, but adds no syntax or default detail beyond the schema; baseline 3 applies.

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+resource (opens a live voice interview with Alex, GoNoGo's AI mentor) and names the concrete outcome (market/competitor research plus a GO / NO-GO verdict with reasons). It is unmistakably distinguishable from the siblings get_project_result, list_my_projects and whoami, which are account/result lookups.

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?

It gives explicit triggering scenarios (validate a startup idea, decide whether to quit a job, rehearse investor/accelerator questions) and an explicit exclusion list (running an existing business, business plans, naming/branding, coding, legal/tax/investment advice). It also resolves the multi-idea case: one interview per idea, run one for each.

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