reveal_model_answer

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

With no annotations provided, the description carries the full burden. It discloses the tool's output (the casebook's answer), the timing restriction ('Only after grading'), and a behavioral directive (paraphrase conversationally, not verbatim). This adds meaningful context beyond a simple 'returns answer' statement.

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 exactly two sentences, with the core purpose front-loaded. Every clause adds value: the first sentence states what the tool provides, the second gives timing and usage guidance. There is no redundant or wasted text.

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 an output schema present, the description is highly complete. It covers what the tool does, when it is appropriate to use it, and how the returned answer should be presented. The existence of an output schema covers return-value specifics, so the description does not need to explain those.

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 schema is empty (100% schema description coverage). The baseline for 0 params is 4, and the description does not need to explain parameter semantics. It appropriately focuses on the tool's purpose and usage.

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 function: revealing the casebook's own answer for the current question. It uses a specific verb ('reveal') and resource, and distinguishes itself from siblings by specifying the timing ('after grading') and the intended pedagogical use.

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 explicit usage direction: 'Only after grading' is a clear when/when-not constraint, and 'Use it to explain what a strong answer sounds like' defines the intended context. It also provides delivery guidance by instructing to paraphrase rather than read verbatim, which is a strong usage guideline.

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