model_tool

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

No annotations are provided, so the description carries the full burden. It discloses a key behavioral trait: 'without loading into memory', which indicates a non-destructive, memory-efficient operation. However, it does not mention other behavioral aspects such as output format, error handling, or whether the tool requires special permissions, leaving some uncertainty for a tool with no annotation support.

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?

The description is a single, well-structured sentence followed by a concise list of operations. It front-loads the main purpose and gives operation details without wordiness. Every clause contributes to understanding the tool's scope and capabilities.

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?

Given the tool has 9 parameters and no output schema or annotations, the description provides a solid high-level overview of all operations and their intents. While it omits details like defaults (recursive) or the shape of returned data, the schema covers parameter semantics, and the description effectively ties operations to their purposes, making it adequate for a multi-operation tool with a rich schema.

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%, so the baseline is 3, but the description adds value beyond the schema by explaining the operation enum and mapping operations to their parameter needs (e.g., 'compare' uses path1/path2, 'search' uses query, 'list' uses path). This operational context helps the agent select and combine parameters correctly, exceeding the schema's individual field descriptions.

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 begins with a specific verb-resource pair: 'Inspect AI model files (Safetensors/GGUF)', clearly distinguishing this from sibling file tools (efs_*, etc.) by focusing exclusively on model file types. It further enumerates four concrete operations (info, list, compare, search), making the tool's purpose unambiguous and non-overlapping with siblings.

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 description provides clear context: use this when you need to inspect or gather metadata about AI model files without loading them into memory, and it lists the operations available. However, it does not explicitly state when NOT to use it or mention alternative tools (e.g., efs_read for general file reading), so it falls short of a 5 for explicit exclusions.

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