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download_local_model

Downloads a catalog model or Hugging Face repo into the allowlisted models directory. Requires an explicit model_id; uses HF_TOKEN for gated repos. dry_run checks the destination path.

Instructions

Download a catalog model (or Hugging Face org/name repo) into the allowlisted models directory (default .orchestrator/models). Large; requires an explicit model_id. Honors HF_TOKEN / HUGGING_FACE_HUB_TOKEN for gated repos. dry_run only checks the destination path.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
destNoOptional destination directory; must be inside the write allowlist
dry_runNoValidate allowlisted path only; do not download
model_idYesCatalog id from list_local_models, or a Hugging Face repo id
Behavior4/5

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

With no annotations, the description carries the transparency burden and does well: it discloses the allowlisted destination, size implication, reliance on HF_TOKEN/HUGGING_FACE_HUB_TOKEN for gated repos, and the limited scope of dry_run. It does not mention overwrite behavior or return details, but the disclosed traits are meaningful.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four short sentences deliver purpose, destination, warnings, auth, and dry_run behavior with no filler. The most important scoping information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 3-parameter download tool with no annotations, the description is nearly complete: it covers destination, auth, and dry_run. It could add what the tool returns or whether it overwrites existing files, but nothing required for a safe first invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is already 100%, and the description adds value on top: it supplies the default destination directory, clarifies that model_id can be a catalog id or HF repo id, and explains dry_run semantics beyond the schema's one-liner.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a precise operation: download a catalog model or HF repo into the allowlisted models directory, with a default path. This clearly separates it from local-model management siblings like delete_local_model or list_local_models.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives clear usage context: use it for large model downloads into the allowlisted directory, pass an explicit model_id, and use dry_run to validate the destination. It does not explicitly contrast with alternatives or state when not to use it, so it misses the full when/when-not guidance.

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

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