tool_embed

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

No annotations are provided, so the description carries the full behavioral burden. It discloses only that a float vector is returned; it says nothing about vector dimensionality, cost/quota implications, authentication requirements, or whether the call is idempotent/cacheable. For an un-annotated tool this is a meaningful 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?

A single, front-loaded sentence with the verb and output type leading. It is efficient with no wasted clauses, though it is arguably under-specified rather than truly concise.

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 simple single-input embedding tool with no output schema and no annotations, the description covers the core purpose but omits output shape (dimension/size of the vector), model selection implications, and any usage context, leaving the agent to infer more than it should.

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 description adds no parameter information at all. Reported schema description coverage is 0%, and while the nested schema does carry some per-field text, the description does not compensate by explaining the text input or the model override, which is the one field an agent would most need contextualized.

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 states a specific verb and resource ('Generate a float embedding vector') plus the provider ('Gemini Embedding'), which is enough for an agent to distinguish it from the media-generation siblings (images, video, music, speech). It does not explicitly name or contrast against any sibling, but the embedding task is inherently distinct.

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?

There is no guidance on when to use embeddings versus other tools, no mention of batch vs single-text usage, no note about when to prefer this over other analysis tools, and no prerequisites or constraints. The agent gets the what but not the when.

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