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

With no annotations, the description carries the full burden and does so well: it discloses that compatibility evidence comes only from product_tag, that relation type comes from product_cat, the exact default availability semantics (stock_autoid > 0 OR stock_distributie > 0), AutoID-stock prioritization, and that out-of-stock items are omitted by default. Auth requirements and rate limits are unstated, keeping it from a 5.

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?

Front-loads purpose, then layers behavioral detail in dense but information-bearing sentences. Slightly long, but nearly every clause adds a distinct behavioral or filtering fact rather than restating the schema.

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 6-parameter tool with no output schema and no annotations, the description is largely sufficient: it covers filtering semantics, defaults, ordering, and return-card pricing fields (pricing.ron_display, inc-VAT preference). Minor gaps remain around pagination guidance and error/permission behavior.

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 only 50%, and the description compensates by explaining target (model/group SKU or exact product SKU), enumerating relation_type values, and unpacking availability's default and out-of-stock behavior. It also clarifies category as an exact WooCommerce slug with concrete examples. limit/offset semantics are left to 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?

States a specific verb and resource ('Returns first-party related catalog entities for a model or exact SKU') with clear scope and evidence sources. It is distinguishable from get_product/search_products by its related-entity focus, but it never names a sibling to sharpen the boundary (e.g., get_related_products_summary).

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?

Gives strong operational guidance on parameter usage ('request availability=out_of_stock or availability=all explicitly if needed', 'Use category ... to narrow large sets'), but offers no tool-selection guidance relative to alternatives. When to reach for this versus get_related_products_summary or get_product is left to inference.

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