variant_flattener_endpoint_v1_enrich_variant_flattener_post

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

With no annotations provided, the description is the sole source of behavioral information. It does disclose the cost ('2 credits per request'), which is a useful behavioral detail. However, it does not state whether the operation is read-only, side-effect free, or what the output format looks like. Given the tool's generative nature, the absence of explicit non-destructive statements and output details leaves transparency incomplete, but the cost disclosure earns a 3.

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 sentences long and front-loads the core purpose in the first sentence. The cost is a secondary detail placed after the purpose. While it is concise and well-structured, it could have included a brief note on expected output, but it is not overly verbose. A 4 reflects the efficient and purposeful structure.

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?

The tool has three parameters (two required nested objects) and no output schema. The description explains what it does (generates combinations) but does not describe the return format, limits, or any prerequisites beyond the schema. For a tool that produces a potentially large Cartesian product, the absence of output details and any caveats (e.g., handling of empty option lists) makes it only minimally sufficient. Given the schema richness, a 3 is appropriate.

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?

Input schema coverage is 100%, meaning every parameter (variants, base_product, sku_format) has a description and example. The tool description itself adds no parameter-level details beyond what the schema provides. Per the calibration baseline, with high schema coverage a 3 is appropriate because the schema does the heavy lifting.

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: 'Generates all possible combinations (Cartesian product) from a base product and lists of variant options.' This is a specific verb ('generates') and resource ('combinations'), and it distinguishes the tool from most siblings (e.g., enrich_* tools) by its exclusive focus on variant generation. The mention of E-commerce and ERPs further clarifies the domain.

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 says the tool is 'Useful for E-commerce platforms (Shopify, WooCommerce) and ERPs,' providing context for when it might be applied. The schema field for 'variants' explicitly says 'USE THIS TOOL to generate all possible SKU combinations,' which is strong usage guidance. However, it does not mention when not to use it or name alternative tools (none of the siblings appear directly comparable), 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.