model_rm

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

No annotations are provided, so the description bears the full burden. It discloses that the tool only removes native models it downloaded and that Ollama/LM Studio models are read-only (implying the operation will fail or be no-op). This is good behavioral disclosure, though it does not detail error handling or side effects beyond that constraint.

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 relatively concise and front-loaded with the primary purpose. It uses a docstring-style structure with 'Args' section, which is clear. There is no unnecessary verbosity, though some minor elaboration on error cases could be added without breaking conciseness.

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 (removing a model with two parameters) and the presence of an output schema (implied by 'Has output schema: true'), the description is largely complete. It covers the main behavior, parameters, and constraints. It could mention potential error scenarios or return values, but the output schema likely handles that. Overall, it provides sufficient context for an agent to select and use the tool correctly.

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 adds meaning beyond the input schema by explaining the 'model' parameter as 'Model ref to remove' and noting the read-only context for certain model types. For 'source', it clarifies its purpose and default behavior. Even though the context signal indicates 0% schema description coverage, the description effectively compensates for this gap.

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 'Remove an installed model' with a specific verb and resource. While it is clear, it does not explicitly differentiate from the sibling 'remove' tool, which might have overlapping functionality. However, the tool's name 'model_rm' and its description make the purpose clear.

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 explicit guidance on when to use the tool (for native models that lilbee downloaded) and when not to (for Ollama and LM Studio models, described as read-only). It also explains the 'source' parameter, advising to restrict to a known source or leave empty for resolution. This fully informs the agent about appropriate usage contexts.

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