recommend_docs_path

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds substantial behavioral detail beyond annotations: 1.5x boost for product_hint matches, deduping across products, top-heading rationale, pre-built top-2 citations, and the NO_DOCS_MATCH error behavior. This is exactly the kind of context that helps an agent predict execution semantics.

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 long but appropriately structured: core behavior first, then when-to-call, input requirements, and output shape. Every section earns its place given the composite nature of the tool and the lack of an output schema. No filler or tautological 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?

Given no output schema, the description fully documents the return shape, including the recommended array, by_product summary, related_docs citations, and the zero-match error structure. It also covers when to use it, input constraints, and the ranking boost behavior, making it complete enough for reliable invocation.

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 the baseline is 3, but the description meaningfully exceeds it. It explains the intent style recommendation ('Drop verbs and use product nouns'), the effect of product_hint as a 1.5x score multiplier, and the merging cap behavior of limit_per_product. This adds practical semantics beyond the raw schema field descriptions.

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 uses a specific verb and resource: it fans out parallel scoped searches across all four DERO product docs and returns a ranked recommendation list with rationale and related_docs. It clearly differentiates itself from dero_docs_search by describing the composite behavior and the pre-built citations, so an agent can distinguish it from siblings without opening schemas.

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 'When to call' section is explicit: call at the start of a docs-discovery investigation and BEFORE calling dero_docs_search directly. It also explicitly prefers this over guessing the product and explains when to pass product_hint, giving clear guidance and an alternative.

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