search_models

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

No annotations are provided, so the description carries the burden and does reasonably well: it discloses the return payload (name, description, capability chips, parameter sizes, install status) and a network dependency. It omits failure/offline behavior and rate-limit or pagination context.

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?

Three tight sentences: purpose and workflow first, return shape second, precondition last. No filler and nothing redundant with structured fields.

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 read-only search tool with no output schema, the description covers purpose, the downstream consumer, the shape of returned data, and the network requirement. An agent has everything needed to invoke it correctly.

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 all four parameters are already documented, including the category enum and limit bounds. The description only loosely echoes them ('capability chips', 'already installed'), adding no syntax or format detail beyond the schema; baseline 3 applies.

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?

States a specific verb (search) and resource (public ollama registry at ollama.com), and explicitly frames the result as input to pull_model. The 'public registry' scoping cleanly separates it from local-model siblings like list_models.

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 phrase 'for models to pull_model' establishes the intended workflow and the 'requires internet access' note flags a precondition. It stops short of an explicit when-not or naming the local alternative (list_models) for already-installed families.

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