generate_embeddings

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions regeneration (implying overwrite) and scope (all files), but doesn't detail side effects, cost, authentication requirements, or whether the operation is idempotent. This is a moderate gap.

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, front-loaded with the action and resource, and every word adds value. No redundancy or filler.

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 tool with no output schema and 3 optional parameters, the description is largely complete: it states scope, action, and outcome. However, it could add context about when to run it (e.g., after knowledge updates) and any caveats, but overall it's sufficient for a straightforward batch operation.

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 already describes all three parameters (verbose, projectName, forceRegenerate) with 100% coverage. The description adds no parameter-level detail, so it neither helps nor hinders beyond the schema, earning the baseline 3.

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 verb (generate/regenerate), resource (vector embeddings), and scope (all Cursor-Cortex knowledge files). It also explains the outcome (enables semantic search), distinguishing it from sibling search tools like comprehensive_knowledge_search.

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 implies usage (generate embeddings to enable semantic search) but provides no explicit guidance on when to run it, such as after updating knowledge files, or when not to use it. It also doesn't mention alternatives, though the tool's purpose is fairly distinct from siblings.

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