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

Annotations declare readOnlyHint=false and openWorldHint=true but say nothing about persistence or dedup. The description fills that gap by clarifying already-tracked prompts are filtered out and 'Nothing is tracked until you create it,' which is valuable for a generically non-read-only tool. It does not mention generation cost/credits or return format, keeping it short of a 5.

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 the core action and a compact Args block. Slight redundancy: 'generic, buyer-style category queries' is restated by 'tuned to ... generic category demand, not branded lookups,' but the repetition reinforces a key constraint rather than bloating meaninglessly.

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?

No output schema exists, so the description is the only source of return-value context and it gives enough (count controlled by limit, new-only results). Safety/side-effect profile is clarified via the explicit 'nothing is tracked until you create it' note, though the exact suggestion payload shape is left implicit.

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?

With schema description coverage at only 25%, the description carries the burden and does: it defines brand_id (required, the brand to target), focus (steering topic, omit for breadth), and limit (1-10, default 8). Only user_intent is undocumented here, but the schema already supplies its own description.

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 (suggest) and resource (AI-search prompts) plus the scope: generic buyer-style category queries a customer would ask an AI, filtered to untracked ideas. An agent can distinguish this from list_prompts or manage_prompt at a glance.

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?

Explicitly says 'Prefer this over inventing prompts yourself' and names the downstream tools (manage_prompt(action="create") / bulk_manage_prompts(action="create")) needed to actually persist prompts. It also states when to use focus (product line/use-case) vs omit it (broad coverage).

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