gsc_content_gaps

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

With no annotations, the description carries the full burden of disclosure. It transparently describes the tool's output (queries with impressions and poor ranking) and imposes explicit constraints on agent behavior (base analysis only on data, avoid speculation, admit insufficient data). It also mandates a rich interactive presentation, which goes beyond the bare data return. However, it omits operational details like authentication or rate limits.

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 structured into clear sections: purpose, analysis constraints, and presentation requirements. It is front-loaded with the core purpose. While the PRESENTATION section is lengthy, each sentence serves a functional purpose in guiding the agent's output, and the overall structure is organized and scannable.

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, the description does a good job of explaining the expected data (queries matching a condition) and sets comprehensive expectations for analysis and presentation. It covers the tool's logic and constraints, though it does not enumerate the exact output fields, which would be useful for complete clarity. For a tool with four optional parameters and no output schema, this is a solid and complete description.

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 description coverage is 100%, so the baseline is 3. The description reinforces the semantic meaning of key parameters ('rank beyond position 20' for min_position, 'where you get impressions' for min_impressions) but does not add new syntax or examples beyond the schema.

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 opens with a specific verb and resource: 'Find topics you should create content for.' It clearly defines the tool's functionality by specifying the exact condition (impressions but rank beyond position 20), which distinguishes it from sibling tools like gsc_quick_wins or gsc_ctr_opportunities.

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 clear context for when to use the tool ('Find topics you should create content for') and gives detailed instructions on how to handle the results (analysis rules, presentation). It does not explicitly mention alternatives or exclusions, but the context is strong enough to guide appropriate use.

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