find_missing_topics

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

No annotations exist, so the description carries full burden for behavioral disclosure. It mentions returns (covered, missing topics, coverage) but does not disclose how SERP competitors are fetched, potential rate limits, whether the tool is read-only, or any dependencies on external data.

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 sentence that efficiently states the purpose and return types. It is front-loaded with the action and avoids extraneous words.

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?

Given no output schema and no annotations, the description adequately states inputs and outputs but lacks behavioral context like processing time, data source reliance, or usage constraints. It is minimally viable but has significant gaps.

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% with clear parameter descriptions. The description adds value by introducing the concept of 'SERP competitors', explaining how the keyword is used beyond just targeting. This partial addition of context raises the baseline above 3.

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 the tool finds topics from SERP competitors that are missing in content. It uses a specific verb-resource combination and distinguishes from sibling tools like analyze_keyword or score_content by focusing specifically on competitor topic gap analysis.

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 implies usage for identifying missing topics in content relative to competitors, which is clear context. However, no explicit when-not-to-use or alternatives are provided, though the sibling tool list helps the agent infer.

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