update_model

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

With no annotations, the description fully discloses the mutation behavior: 'rewritten' and 'reloaded' the .nlogox file, and that widgets are 'preserved unchanged' when omitted. This goes beyond the schema.

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?

Two sentences, front-loaded with the main action, followed by the benefit over the alternative. No extraneous information.

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 simple 2-parameter schema and presence of an output schema, the description covers purpose, usage, behavioral effects, and parameter default behavior (widgets preserved). No 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?

Schema coverage is 100% with detailed descriptions for both parameters. The tool description adds some context (e.g., 'in place' implying file rewriting) but does not significantly enhance the meaning of individual parameters beyond what the schema provides.

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 verb ('Update') and resource ('currently loaded model's code'), and explicitly distinguishes it from the sibling 'create_model' by stating when to prefer this tool ('when iterating on an existing model').

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 explicitly advises to 'Prefer this over create_model when iterating on an existing model', providing a clear use case and rationale (same file rewritten, window stays on model, no directory growth).

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