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

With no annotations provided, the description carries the full burden of disclosing behavior. It explains the vector similarity mechanism, the lack of LLM involvement, and the return format (scored chunks with deep-link URLs). It does not mention rate limits, errors, or pagination, but these are less critical for a read-only search tool.

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, front-loaded with the core purpose, then provides a comparison to search_posts, and ends with the output format. Every sentence adds value, and there is no wasted wording or repetition of schema details.

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 description is complete for a search tool of this complexity. It specifies the scope (blog posts and projects), the search behavior (semantic similarity), the differentiation from a sibling tool, and the return format. Since an output schema exists, the description appropriately does not need to detail the full response structure.

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%, so the description must compensate for parameter semantics. It does not explicitly define 'query' or 'limit', but the query's role is implied by the semantic search context, and the schema provides full constraints and default for limit. The description adds some conceptual meaning about how the query behaves (semantic matching) but leaves limit unexplained 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 performs semantic (vector similarity) search across blog posts and projects, using a specific verb and resource. It also distinguishes this tool from sibling search_posts by contrasting semantic matching with exact substring matching, making the purpose unmistakable.

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 provides explicit usage guidance by naming the alternative (search_posts) and explaining when this tool is broader and more appropriate for conceptual matches. It also clarifies that this is the same retrieval used by the Ask chatbot but without the LLM call, giving clear context for when to choose this tool over others.

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