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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It communicates that the tool exposes all questions, options, and verdicts, which conveys a read-only, complete-content behavior. It does not describe the structure, size, or any potential caveats, but for a static reference tree this is a moderate gap.

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 a single, well-formed sentence that front-loads the core idea ('Every question, option and verdict') and adds only the relevant purpose. No filler or 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?

For a zero-parameter tool with no output schema, the description is reasonably complete: it states the contents and suggests a use case. It could mention the return format or that it is a static dataset, but the simplicity of the tool makes the existing description adequate.

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 tool has zero parameters, and the input schema is empty with 100% coverage. Per baseline, a 4 is appropriate since there are no parameter meanings to clarify, and the description correctly implies no input is needed.

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 identifies the resource (the entire decision tree) and its content (every question, option, verdict). The phrase 'whole decision tree' differentiates it from sibling tools like checker_start and checker_answer without needing to name them, though it stops short of explicitly stating a verb like 'retrieves'.

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 phrase 'for reasoning end to end' implies this tool is appropriate when an agent needs the complete tree in one shot, rather than stepping through it one node at a time. However, it does not explicitly state when to use it over checker_start or checker_answer, nor does it provide exclusion criteria.

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