compute_embeddings

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

Annotations indicate mutation (readOnlyHint=false), but description does not disclose side effects, permissions, or whether results are overwritten. The force parameter is not mentioned.

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?

Concise with two sentences and args list. No waste, but could benefit from structured breakdown of the embedded parameter object.

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?

Despite output schema existing, the description omits return value explanation, prerequisites, and usage patterns for a complex tool with many parameters. Incomplete for its complexity.

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?

Description briefly explains params as 'Embedding parameters (PCA, UMAP, clustering, etc.)'—adds high-level context but lacks detail. Schema descriptions are rich, so moderate score.

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?

Clearly states it computes dimensionality reduction, clustering, and neighbor graphs. Specific verb and resource, but lacks distinction from sibling tools like preprocess_data.

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?

No guidance on when to use this tool vs alternatives like analyze_trajectory_data or preprocess_data. No context on prerequisites or typical use cases.

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