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

With no annotations provided, the description carries the full burden and does so exceptionally well. It discloses the structured verdict format, the specific blocking/advisory/info classification rules, the rendering limitations that trigger each level, and the fact that parsing is local with no API call. This gives an agent a reliable behavioral model.

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 dense but every sentence earns its place: main purpose, return structure, classification rules, and an important behavioral guarantee. It is front-loaded with the core purpose and avoids filler or repetition.

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?

The tool has one parameter, no output schema, and no annotations, yet the description explains what the returned verdict will contain and what conditions trigger each outcome. An agent has enough context to call the tool and interpret its result without ambiguity.

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% for the single 'code' parameter, and the schema already documents it as FlowZap Code to inspect. The description adds context about local parsing and Mind Map readiness, but it does not need to add much more given the high coverage and simple parameter shape.

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 states a specific operation—checking FlowZap Code for suitability to Mind Map rendering—and clearly distinguishes this from a general validation or mutation tool by describing the verdict output and rendering-specific rules. It is not a tautology and the resource and intent are immediately clear.

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 clearly establishes the context for use: checking whether already-valid FlowZap Code is Mind Map-ready, and it explains the outcome categories. It does not explicitly name alternative sibling tools or state when not to use this tool, so it stops short of full when-to-use versus alternative guidance.

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