grain_content_recommendations

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

With no annotations provided, the description must fully disclose behavioral traits. It states 'returns actions' but does not explicitly confirm whether the tool mutates data or is read-only. No side effects, authentication needs, or rate limits are mentioned, leaving significant uncertainty.

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 short sentences that front-load the core purpose with a clear verb and resource. Every sentence adds value without redundancy, making it efficient for an AI agent to parse quickly.

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 has three parameters, no output schema, and no annotations, the description should provide richer context. It explains what it does but omits return format, prerequisites, or when to use it among many sibling tools, leaving the agent underinformed.

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 covers 100% of parameters with descriptions (siteUrl, days, maxRecommendations). The tool description adds no additional explanation for these parameters beyond what the schema already provides, so the baseline score of 3 applies.

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 generates prioritized SEO recommendations by cross-referencing quick wins, content gaps, and cannibalization, and explicitly lists return types (update/create/consolidate actions). This distinguishes it from generic recommendations tools like sibling seo_recommendations by specifying the cross-referencing approach.

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 does not provide any guidance on when to use this tool versus alternatives, such as prerequisites, exclusions, or scenarios where it is not appropriate. The agent has no context to decide between this and similar SEO tools like seo_quick_wins or seo_cannibalization.

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