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

With no annotations, the description carries the behavioral burden. It clearly discloses the output scope (all questions, options, verdicts) and the purpose (end-to-end reasoning), making it evident this is a read-only content accessor. It does not discuss return formatting, but for a zero-parameter static data tool this is a minor omission.

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?

One clean sentence with no filler; the core content scope ('Every question, option and verdict') is front-loaded before the purpose clause. The title reinforces it 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?

For a parameterless tool with no output schema, the description is largely complete: it names the guide, the included elements, and the intended reasoning use case. The only missing piece is an explicit statement of return format, which is not critical given the simple static nature.

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 input schema has zero parameters and 100% coverage, so the baseline is 4. There are no parameters for the description to elaborate, and the tool's no-input nature is consistent with 'the whole decision tree'.

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 exactly what the tool provides: every question, option, and verdict in the named decision-tree guide, for end-to-end reasoning. The 'whole decision tree' scope clearly distinguishes it from sibling tools like checker_answer and checker_start, which cover narrower steps.

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?

Use is implied by 'whole decision tree' and 'for reasoning end to end' — an agent can infer this is for full-tree context rather than a single step. However, no explicit when-to-use or when-not-to-use guidance is given, and alternatives like checker_answer or checker_start are not named.

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