ollama_pull_model

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

Annotations indicate write, idempotent, non-destructive. Description adds file size range, idempotency verification, authentication, rate limits, execution time, error behavior. No contradictions with annotations.

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?

Description is eight sentences, each adding value, with front-loaded purpose and clear structure. No redundancy or fluff.

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?

Covers usage, behavior, constraints, and error handling. Output schema exists, so return value details are not required. Comprehensive for a download tool.

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 coverage is 100% with detailed parameter description. The tool description does not add meaning beyond the schema, so baseline score of 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?

The description specifies downloading a model from the Ollama library to the local machine, using a clear verb and resource. It distinguishes from sibling tools by stating when not to use it (e.g., for inference or when model is already present).

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?

Explicitly states when to use (model needed but not installed) and when not to use (if already installed, use ollama_list_models first; for inference, use ollama_chat or ollama_generate). Provides clear alternatives.

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