wafle_ai_categorize

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

With no annotations, the description carries full burden. It discloses the job-based workflow ('Accept the job to write category overrides') and the return format (`{ category, confidence }` or null), which is valuable beyond what the schema provides.

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 three sentences covering purpose, input, output, and workflow with no redundant words. It is compact and front-loaded.

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 3-param tool with no output schema, the description covers input, output, and the job acceptance step. It omits details on how to accept the job, but sibling tool names (e.g., wafle_ai_jobs_accept) make that inferable.

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 coverage is 100%, so parameters are fully documented. The description adds the output format but does not deepen semantics for slug, product_skus, or available_categories 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 clearly states the tool's function: 'Auto-classify products without a category'. This uses a specific verb and resource, and distinguishes it from sibling AI tools like wafle_ai_translate or wafle_ai_product_describe by focusing on category assignment.

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 direct call instructions ('Call with a list of SKUs and a list of allowed categories') and scopes the use case to products without a category. However, it does not explicitly contrast with alternative tools or state when not to use it.

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