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

Goes well beyond the annotations: discloses that nothing is persisted, that each call regenerates the list, the rate limit (10 calls/min per workspace), dedup against active and retired questions, and enumerates the state values (ready, failed, intelligence_off, no_context) with their meanings. Annotations only cover safety; the description carries the operational detail.

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, and most clauses carry real information. However it is a single dense paragraph mixing purpose, sources, dedup rules, state enum, rate limit and related tools, which hurts scanability and readability.

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?

Even though an output schema exists and would carry return values, the description proactively explains the state enum and source values. For a zero-parameter, read-only suggestion tool, nothing an agent needs to call it 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?

The tool takes zero parameters, so the baseline is 4 and there is no parameter semantics to add. The description correctly signals this is a no-argument call by never introducing inputs.

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?

States a specific verb and resource (suggests buyer questions to track in AI answers) and pins down scope ('up to 10', 'the same list the empty AI answers tab shows'). An agent can distinguish this from get_buyer_question_answers or save_strategy_item without opening a 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?

Gives clear context (starting a buyer-question list, mirroring the empty AI answers tab) and routes the agent to the right follow-up tool: 'add the ones you pick with save_strategy_item (kind buyer_question, fields.question)'. It also lists related tools, though it never states an explicit when-not-to-use condition.

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