get_ia_recommendations

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only states a high-level purpose. It does not describe the output format, how the 'tasks' parameter affects results, or whether this is a read-only advisory action.

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?

A single sentence that is front-loaded with the purpose and includes a concise list of supported guidance types. No redundant or filler content.

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 tool with no output schema and no annotations, the description is thin on behavioral expectations (what does 'guidance' look like?). It also does not explain how to interpret or apply the recommendations, and the optional 'tasks' parameter is not mentioned in the 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?

The input schema documents the 'tasks' parameter with a clear example (100% schema coverage), so the baseline applies. The description does not add any additional meaning or usage context for the parameter.

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 provides information architecture guidance and lists specific sub-services (top task analysis, card sorting, tree testing, navigation best practices). This distinguishes it from sibling tools like get_principles or audit_conversion, though the verb 'Get' is somewhat generic.

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?

No explicit guidance on when to use this tool versus alternatives. The description implies usage for IA-related questions but does not mention exclusions or when another tool (e.g., recommend_layout) would be more appropriate.

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