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

With no annotations, the description must carry the full behavioral burden; it does disclose fuzzy ranked matching and the return fields (title, URL, category, summary, relevance score), which is real value. It says nothing about indexing freshness/reindex interaction, ranking behavior details, or whether results are version-scoped.

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?

Three short sentences: purpose first, usage condition second, return shape third. Nothing redundant, nothing buried.

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 return-value gap is covered since no output schema exists, and usage is framed well. However, for a tool with four undocumented parameters and no annotations, omitting any parameter guidance leaves an agent guessing on filtering and result-count semantics.

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 description coverage is 0% across four parameters, so the description must compensate and does not: it never mentions query, top_k, version, or category. Notably top_k is typed as a string, and the description offers no clarification on its acceptable values, nor on what version/category restrict.

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 ("Fuzzy-search the Duck Framework documentation") and even specifies the matching mode (fuzzy, ranked). It implies a contrast with direct-lookup siblings like get_component_api but never names one, so differentiation is inferred rather than stated.

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?

"Use this whenever the correct documentation page for a feature is unknown" is a genuine when-to-use condition that routes discovery-style queries here. No explicit when-not or named alternative (e.g., list_doc_categories for browsing) is given.

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