generate_contentGenerate AI-optimized content (FAQ, about copy, use cases, differentiators) for the gaps in your latest scan. Returns full content text inline — no need to visit the dashboard. Pro plan or higher required. Pass gap_type='all' to get every block in one call.
| Name | Required | Description | Default |
|---|---|---|---|
| gap_type | Yes | Which content block to generate. Use 'all' for everything in one call. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since annotations provide no useful hints (all false), the description carries the burden. It discloses that content is returned inline (no dashboard visit required), the Pro plan requirement, and the behavior of gap_type='all'. This adds meaningful non-obvious context beyond the annotations.
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 two succinct sentences: the first states the core purpose and content types, the second adds key behavioral details (inline return, plan requirement, 'all' option). Every sentence earns its place with no redundancy or fluff.
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 the tool's low complexity (one parameter, no output schema, no nested objects), the description is complete. It covers purpose, output format, access requirements, and special parameter values, so the agent has enough to invoke it correctly without additional documentation.
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 schema description provides complete coverage (100%) for the single parameter gap_type, including all enum values and an explanation for 'all'. The description only repeats the 'all' hint, adding no extra semantic value beyond what the schema already offers, so the baseline of 3 is appropriate.
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's function: generating AI-optimized content (FAQ, about, use cases, differentiators) for gaps in the latest scan. The verb 'generate' and specific content types make the purpose distinct from sibling tools like list_content_gaps or scan_visibility.
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 gives clear usage context: it's for gaps in the latest scan, requires a Pro plan or higher, and provides a shortcut for getting all blocks at once (gap_type='all'). However, it doesn't explicitly mention when not to use it or name alternatives, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a unique aspect of brand visibility management: scanning, auditing, listing gaps, generating content, and retrieving scores. No two tools overlap in function.
All tool names follow a consistent verb_noun pattern using snake_case (e.g., scan_visibility, get_latest_score). This makes it easy for an agent to infer action and target.
With 5 tools, the server covers the core workflows of scanning, auditing, content gap analysis, content generation, and score retrieval without being bloated or sparse.
The tool surface provides a complete lifecycle for brand visibility analysis: scan → audit → identify gaps → generate content → get score. No obvious missing operations.