get_seo_recommendations

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

With no annotations, description should compensate; it states it does not run Lighthouse, which is useful, but does not disclose other behaviors like whether it is a simple query or requires prior setup, or what the response format is.

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 concise with two sentences: the first states the purpose and scope, the second clarifies a key differentiator. No filler.

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?

For a simple tool with one optional parameter, the description covers purpose, scope (React/Next.js), and key differentiator (no Lighthouse). It lacks explicit mention of output structure, but context signals show no output schema, so it's acceptable.

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 fully documents the parameter, but the description adds context (React/Next.js specific, no Lighthouse) that clarifies the tool's scope beyond the enum values.

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 returns SEO, performance, and accessibility recommendations for React and Next.js projects, explicitly noting it does not perform Lighthouse analysis, which distinguishes it from sibling tools like lighthouse_analyze and compare_lighthouse.

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 sets a clear context (general best practices without Lighthouse) and implies use cases (SEO, performance, accessibility), but does not explicitly state when not to use or direct to specific siblings, which is mildly lacking.

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