validate_material_graph

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

With no annotations, the description carries the full burden. It discloses that the tool is non-destructive (diagnoses), categorizes nodes, and returns a boolean `healthy`. It does not detail authorization needs or side effects, but the behavior is adequately explained.

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 concise and well-structured: a one-sentence purpose, bullet-like categorization, and a clear return value indication. Every sentence adds value without redundancy.

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 presence of an output schema, the description satisfactorily explains the return logic. However, the lack of parameter documentation is a minor gap. Overall adequate for a single-parameter diagnostic tool.

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 only parameter `material_path` has no schema description (0% coverage) and the description adds no additional meaning. It does not specify the expected format or context, leaving ambiguity for the agent.

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 purpose as diagnosing connection issues in a material graph. It lists specific node categories (orphaned, dead_ends, etc.) and their definitions, distinguishing it from sibling tools like `cleanup_material_graph` and `get_material_errors`.

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 implicitly guides usage by explaining the tool's diagnostic role. It does not explicitly state when to avoid using it or name alternatives, but the context of sibling tools provides some guidance.

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