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

No annotations are supplied, so the description carries the full disclosure burden, yet it never states whether the call is a safe read, what it returns (a prompt, a guide, a report?), or how long it runs. 'Includes the complete prompt, usage guide, and edge-case handling' hints at static content delivery but does not clarify whether output is a template or an analysis. No limits, permissions, or side effects are mentioned.

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?

Three sentences are spent on promotional framing ('produce professional results in minutes') before any functional information, and the closest thing to a purpose statement appears in the middle. Words like 'Turn expertise into output' earn no place in a tool definition. Front-loading is absent.

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 tool itself is simple (one optional param, no output schema), so completeness should be easy to achieve, yet the agent still does not know what invoking it produces or when to prefer it. With no annotations and no output schema, the description is the only source of this information and it omits it entirely.

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 single parameter is fully documented in the schema, including that it is optional and scopes the analysis, so the baseline of 3 applies. The description adds nothing about how 'query' shapes the result, but with 100% schema coverage it does not need to. No enum or format ambiguity exists.

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 text reads as marketing copy for a 'prompt pack' rather than a statement of what the tool does. It never says whether the tool performs research, returns a prompt template, or generates a report; 'Turn expertise into output' is a slogan, and 'social media research' is only restated via the name. An agent cannot distinguish this from siblings such as ai-search-monitor, xiaohongshu-search, or community-viral-event.

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 when-to-use guidance, no prerequisites, and no named alternative among the hundreds of siblings. The only context given is an audience hint ('restaurant and brand teams'), which is not an invocation condition. Nothing tells the agent when to pick this over the many adjacent research/monitoring tools.

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