model_provenance

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

With no annotations, the description carries full burden. It discloses that the tool is a read operation and compares digests, but does not mention what happens on drift (e.g., generates a report, returns a list), any authorization needs, or side effects. It's adequate but could be more transparent.

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 very concise, with two sentences plus arg explanation. It is front-loaded with [READ] and the core action. Every sentence is meaningful without redundancy.

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's simplicity and lack of output schema, the description covers the primary functionality. However, it omits details about the output format (e.g., list of models with drift status) and any prerequisites (e.g., the model must be pinned). It is complete enough for a straightforward tool but has gaps.

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?

The description explains the 'target' parameter: 'Ollama target name from config; omit for the default.' This adds meaning beyond the schema's type and default. Although context shows 0% schema description coverage, the description effectively documents the parameter.

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 clearly states the tool's action: 'Compare each installed model's digest against its pin; flag drift.' The [READ] prefix indicates it's a read operation. It distinguishes itself from sibling tools like list_models or running_models by focusing on integrity validation.

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 implies usage for checking model integrity, but it does not explicitly state when to use this tool versus alternatives (e.g., when to suspect tampering or after pulling models). No when-not-to-use guidance is provided.

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