validate_embeddings

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

No annotations are provided, so the description bears full responsibility. It states the tool returns validation status and details, but lacks specifics on side effects (likely read-only), rate limits, or database interaction. This is adequate for a simple check but could be richer.

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 with three sentences. The first sentence front-loads the purpose, and subsequent sentences add necessary context. Every sentence contributes value without redundancy.

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 zero-parameter tool with an output schema, the description is sufficient to understand its function and context. It could mention that it's a safe read operation, but the simplicity of the tool reduces the need for more.

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 no parameters, and schema description coverage is 100% (trivially). The description implicitly clarifies that no parameters are needed because the tool checks internal state, but adds no further parameter semantics 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 checks if the embedding model has changed since database creation, specifying the action and resource. It differentiates from siblings like embedding_info or db_info by focusing on change detection and compatibility implications.

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 explains when to use the tool (when model or dimension might have changed) and hints at consequences (need for re-embedding). However, it does not explicitly exclude scenarios or compare to siblings like db_maintenance.

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