blender_find_problems

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds behavioral context by explaining that the tool returns an 'actionable' list pairing problems with resolving tool calls, which goes beyond the annotations. It does not contradict the annotations, and it provides useful information about the output format.

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 two concise sentences with no waste. The opening comparison to blender_validate immediately orients the agent, and the usage guidance follows directly. Every sentence earns its place, making it easy to parse quickly.

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?

For a read-only validation tool with no output schema, the description explains the return format ('actionable' list pairing problems with fixes) and the usage context. It doesn't detail all parameters, but the schema covers 80% of them. The description is sufficient for an agent to know what to expect and how to use it, though it could mention edge cases like empty results.

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 description coverage is 80%, meaning most parameters have descriptions in the schema. The tool description itself adds little about parameters beyond the schema, mentioning the 'actionable' list but not parameter specifics. With high coverage, the schema handles most semantic burden, so a baseline of 3 is appropriate.

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 function: it's like blender_validate but returns only failures, each with a concrete fix. It also frames the purpose as 'act rather than read', distinguishing it from the sibling validation tool. This gives an agent a precise understanding of what the tool does and how it differs.

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 says 'Use this when you want to act rather than read', providing a clear usage condition. It contrasts with blender_validate, implying that blender_validate is for reading/understanding while this tool is for actionable fixes. However, it doesn't explicitly mention when not to use it, such as when a full validation report is needed.

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