generate_fishbone_diagram

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

No annotations are provided, and the description fails to disclose important behavioral traits such as whether the diagram is interactive, what output format is returned (e.g., image, HTML), or any side effects. This leaves the agent uninformed about runtime behavior.

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 extremely concise: two sentences that efficiently define the tool's purpose and use case. Every word adds value, and the structure is front-loaded with the core definition.

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 complexity of nested parameters and the lack of an output schema, the description should explain what the tool returns (e.g., a chart image URL) and provide a complete example. The truncated example and omission of output format make the description incomplete for a full understanding.

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 the schema already documents parameters well. The description adds an example but the example is truncated and incomplete, which is a negative. Overall, the description does not significantly enhance understanding beyond the schema.

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 it generates a fishbone diagram for displaying causes/effects of a core problem, which differentiates it from other chart types like bar or line charts. However, while it mentions suitability for problems with multiple related factors, it does not explicitly contrast with the similar sibling 'generate_mind_map', which could be used for similar purposes.

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 gives a usage hint ('It suits problems that can be split into multiple related factors'), which helps decide when to use it. However, it lacks explicit when-not-to-use guidance or alternative tool suggestions, such as when a mind map or flow diagram might be more appropriate.

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