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

Annotations already mark the tool as read-only; the description adds value by disclosing the exact data scope: suggestion lists for the seed's prefix, positions 1-10, related vocabulary, and observed marketplaces. It also clarifies output limitations, which is useful beyond the annotation hints. No contradictions.

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 dense but every clause adds information: data returned, use cases, and exclusions. It is slightly run-on and could be broken into clearer sentences, but nothing is wasted.

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?

Since there is no output schema, the description compensates by describing the return contents: suggestion lists with positions, related vocabulary, and marketplaces. It is missing minor details such as empty-result behavior or exact response shape, but for a simple two-parameter read-only read the coverage is adequate.

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 100%, so the schema already documents both parameters. The description reinforces the meaning of seed ('seed term') and marketplace ('per marketplace', 'Amazon marketplaces only') but does not add substantial new per-parameter detail.

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 precisely defines what the tool returns: Amazon autocomplete keyword suggestions for a seed term, with list positions and per-marketplace observation. It also distinguishes itself from volume- or ranking-based keyword tools by explicitly stating those are excluded.

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 use cases ('listing/backend keyword language', 'what do buyers type for X', seeding research) and explicit when-not-to-use boundaries (no volume figures, no organic-ranking data, Amazon only). It does not name an alternative sibling tool, so it stops short of a full 5.

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