download_model

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

With no annotations, the description carries the full burden and does disclose the most important trait: this is an asynchronous background job whose completion must be checked via get_job. It does not mention auth needs (HF token), disk-space/allowed-root constraints for local_dir, or failure behavior, which are relevant for a large download.

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?

One dense paragraph that front-loads the verb, source, and execution model, then supplies a concrete example. Every sentence carries information, though the parenthetical about serving stacks is slightly wordy.

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 download tool with no output schema, the description supplies the essential operational facts: source CLI, async execution, polling tool, and a concrete example. It omits what happens to the artifact on completion and any auth preconditions, which leaves a small gap but not a blocking one.

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, and the description adds only a usage example pairing repo with include. That is a small increment over structured data, so the baseline 3 is appropriate.

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 (download) and resource (a model from Hugging Face) and explicitly differentiates itself from the sibling pull_model ('where pull_model doesn't apply'). An agent can route between the two download paths without opening either schema.

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?

Names the alternative tool (pull_model) and the class of servers where this tool is the right choice, plus the follow-up action (poll with get_job). The selection condition is a bit loose ('llama.cpp/TabbyAPI/vLLM-style servers'), so it stops short of an explicit decision rule but still gives clear context.

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