MCP-Saptiva

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool generates embeddings and lists example applications, but it doesn't disclose key behavioral traits such as rate limits, authentication requirements, response format, or potential costs. For a tool with no annotation coverage, this leaves significant gaps in understanding how it operates.

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 concise and well-structured with two sentences: the first states the core purpose, and the second provides usage context. Every sentence adds value without redundancy, making it efficient and front-loaded for quick understanding.

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 the tool's moderate complexity (single parameter, no output schema, no annotations), the description is adequate but incomplete. It covers the purpose and usage examples but lacks details on behavioral aspects like response format or limitations. Without annotations or an output schema, the description should do more to compensate, but it meets a minimum viable standard.

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?

The input schema has 100% description coverage, with the single parameter 'text' documented as 'Text to convert to embedding vector.' The description adds no additional parameter semantics beyond what the schema provides, such as text length limits or encoding requirements. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't need to.

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's purpose: 'Generate semantic embeddings for text using Saptiva Embed model.' It specifies the verb ('Generate'), resource ('semantic embeddings'), and technology ('Saptiva Embed model'). However, it doesn't explicitly distinguish this from sibling tools like saptiva_batch_embed, which appears to be a batch version of the same function.

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 implied usage guidance by stating 'Useful for similarity search, clustering, and RAG applications,' which suggests contexts where this tool is applicable. However, it doesn't explicitly state when to use this tool versus alternatives like saptiva_batch_embed or saptiva_chat, nor does it provide exclusions or prerequisites for use.

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