update_class

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

With no annotations, the description carries full burden. It discloses the shallow-merge behavior, the warning condition (code 41) when a learned skill lacks a trait, and the ability to replace arrays. It does not mention return values, permissions, or error handling, but provides strong behavioral insight for an update operation.

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?

Three sentences, each earning its place: first defines the operation, second gives usage guidance, third describes a specific warning. No fluff, perfectly front-loaded with the core purpose.

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 3 parameters, a nested object, no output schema, and no annotations, this description covers the essential aspects: what the tool does, when to use it, and key behavioral nuances. It does not explain return values, but for a tool with clear update semantics, this is sufficient. The alternative suggestions further enrich context.

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 baseline is 3. The description adds value by enumerating typical updatable properties (name, expParams, traits, learnings/params) and explaining the shallow-merge semantics, which clarifies how the 'updates' object is interpreted beyond the schema's generic description.

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 updates a class's properties via a shallow merge, with a specific list of use cases (name, expParams, traits, learnings/params arrays). It explicitly distinguishes itself from siblings by recommending add_class_learning and set_class_param_curve for targeted edits, making the purpose highly specific and unambiguous.

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 this tool versus alternatives: use it for general property updates or replacing whole arrays, but prefer targeted tools for individual learnings/param curves. This directly addresses tool selection and avoids misuse.

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