request_user_pick

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does mention the long-poll behavior and the UI dependency, which are valuable traits not visible in the schema. However, it does not cover timeout handling, cancellation, or side effects, so transparency is partial.

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 a single, front-loaded sentence that states the main action and adds key constraints without any redundant information. Every word earns its place.

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?

The description covers the core function and important constraints (long-poll, UI requirement), and an output schema exists. However, it lacks parameter guidance and edge-case behavior, and with no annotations the overall context is only partially complete.

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 0%, and the description only vaguely references 'candidate assets' without explaining the req object, the required candidates array, reason, project_id, or timeout_seconds. The description fails to compensate for the schema gap, providing almost no parameter semantics.

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 clearly states the tool asks the user to directly pick among candidate assets, using a specific verb ('request') and resource ('user pick'). This distinguishes it from sibling tools like suggest_packs or find_asset which do not involve interactive user choice.

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?

The description gives useful usage context: it is a long-poll (5 minutes) and requires the GAH web UI to be running. However, it does not explicitly state when to use this tool versus alternatives like suggest_packs or list_assets, leaving the guidance implied rather than explicit.

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