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

No annotations provided, so description carries full burden. It mentions 'Multilingual' but lacks details on output dimensionality, cost, latency, or side effects. The behavior is minimally disclosed.

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?

Single sentence covering core function and a key feature (multilingual). Efficient and front-loaded, but could include a brief note on output without making it verbose.

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 simple tool with one parameter and no output schema, the description is mostly adequate. However, missing details about the embedding format (e.g., dimensionality) and any usage limitations (e.g., max text length) create gaps.

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 100% for the single parameter. The description adds 'for semantic search / RAG' which mirrors the main description but does not add meaningful new information beyond the schema’s own description.

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?

Description clearly states the tool converts text into numeric embeddings for semantic search, RAG, and similarity. Verb 'embed' and resource 'embedding vector' are specific. However, it does not explicitly differentiate from sibling tools like 'classify' or 'extract_entities', though the function is distinct.

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?

Usage is implied through the mention of semantic search, RAG, and similarity. No explicit guidance on when to use versus alternatives (e.g., 'chat' or 'summarize'), nor any conditions or prerequisites.

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