zerodb_store_vector

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the dimensionality requirement ('exactly 1536 dimensions'), which is a constraint, but fails to cover other critical aspects like authentication needs, rate limits, idempotency, or what happens on success/failure. For a storage tool with zero annotation coverage, this leaves significant behavioral gaps.

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 a single, efficient sentence that directly states the tool's function and key constraint. It is front-loaded with the core purpose and avoids unnecessary details, making it highly concise and well-structured without any wasted words.

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 complexity of a storage operation with no annotations and no output schema, the description is insufficient. It lacks information on return values, error handling, side effects, and how it integrates with sibling tools. For a tool that modifies data (implied by 'Store'), more context is needed to ensure safe and effective use by an AI agent.

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%, so the schema already documents all parameters thoroughly. The description adds minimal value by reiterating the dimensionality constraint for 'vector_embedding', which is also covered in the schema via minItems/maxItems. No additional semantic context is provided beyond what the schema offers, aligning with the baseline for high coverage.

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 action ('Store') and resource ('vector embedding with metadata'), making the purpose evident. However, it does not explicitly differentiate this tool from sibling tools like 'zerodb_store_memory', which might have similar storage functions but for different data types, leaving some ambiguity in sibling distinction.

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 no guidance on when to use this tool versus alternatives, such as 'zerodb_store_memory' or other storage-related siblings. It lacks context on prerequisites, exclusions, or specific scenarios for application, offering only a basic functional statement without usage context.

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