generate_truth_table

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

No annotations are provided, so the description must fully disclose behavior. It only states the action and result, omitting details such as computational intensity, safety limits (though mentioned in schema), or any side effects. The description is too brief to adequately inform the agent about behavioral traits.

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 sentence with 18 words, conveying the core purpose efficiently without redundancy. It earns its place, though it could be slightly expanded for better completeness without losing conciseness.

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 tool's simplicity (2 parameters, no output schema) and the clear description of output (truth table + classification), the description provides sufficient context for basic use. However, it lacks any mention of prerequisites or performance considerations.

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%, so the schema already documents both parameters. The description does not add additional meaning beyond what is in the schema. Baseline score of 3 is appropriate.

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 it generates a complete truth table and classifies the expression as Tautology, Contradiction, or Satisfiable. This distinguishes it from siblings like evaluate_boolean or solve_sat, which have different purposes.

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 implies the tool is used when a full truth table is needed, but it does not explicitly mention when to avoid this tool or suggest alternatives like evaluate_boolean for simple evaluation or solve_sat for SAT solving. No context or exclusion criteria are provided.

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