auto_hashtag_suggestions

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

No annotations are provided, so the description bears the full burden of disclosing behavior. It only mentions that it is AI-powered and analyzes content, but does not state whether it is read-only, requires any authentication, or what side effects (if any) occur. It also doesn't mention how the user should provide media_url or how suggestions are returned.

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 concise sentence that gets to the point. It avoids unnecessary words, though 'AI-powered' is somewhat generic. Overall, it is well-structured and front-loaded.

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?

Despite the simple purpose, the tool has a nested settings object offering multiple options, and no output schema is provided to clarify the response format. The description provides minimal context, leaving the agent uncertain about how to configure suggestions or interpret results. It is insufficient for a tool of this complexity.

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 input schema describes content and media_url adequately, and suggestion_settings has nested property descriptions. The description only reinforces the role of content analysis and adds no information about media_url or the configurable settings like count, style, or industry_focus. With 67% schema coverage, the description could compensate but does not.

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 that this tool generates AI-powered hashtag suggestions from content analysis. It uses the noun 'suggestions' and indicates the input is content. While it doesn't explicitly contrast with sibling tools like search_by_hashtags, the purpose is unambiguous.

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 provides no guidance on when to use this tool versus alternatives. There is no mention of situations where it should not be used or which sibling tool to prefer. For instance, search_by_hashtags is for searching existing posts, but the description doesn't clarify this distinction.

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