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

No annotations are provided, so the description carries the full burden. It hints at a processing path (product idea -> Qloo evidence -> code-made decision), which suggests an analysis rather than a mutation, but it never states side effects, whether the call is read-only, auth requirements, latency/cost, or how the decision is represented. "A decision made by code" is opaque rather than disclosive.

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 short, but the brevity reflects under-specification rather than economy: one arrow fragment with no sentence that actually states what the tool does or returns. Nothing is wasted because almost nothing is said.

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 annotations, no output schema, and 0% parameter documentation, the description is the only source of information and it is a single fragment. The agent cannot determine the return type, the meaning of "decision," the role of `place`, or any usage constraints, making the definition inadequate for a two-parameter 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 description coverage is 0% for both parameters. The phrase "product idea" loosely maps to the required `idea` parameter, but the optional `place` parameter is never mentioned anywhere, so an agent cannot know it controls geography or what format it expects. The description does far too little to compensate for the coverage gap.

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 title ("Is this product wanted?") plus the arrow fragment convey the gist: evaluate demand for a product idea using Qloo evidence and return a coded decision. But the description itself has no verb and never says what the "decision" is or how it is expressed, so the purpose is vague rather than specific. It also does not distinguish itself from siblings like knos_evidence or qloo_where_popular.

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?

There is no statement of when to use this tool versus the many qloo_* siblings (qloo_rank, qloo_where_popular, qloo_recommend) or knos_evidence. No prerequisites, no exclusions, no trigger conditions are given. The agent is left to infer usage entirely from the name.

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