evaluate_boolean

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

No annotations are provided, so the description carries the full burden. It only states that it evaluates an expression but does not disclose error handling, syntax validation, return format, or any side effects. For a tool with no behavioral annotations, this is insufficient.

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-structured sentence that efficiently conveys the tool's purpose and key information (operators). No unnecessary words.

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?

Despite having 2 parameters and no output schema, the description does not explain what the tool returns, how errors are reported, or how it compares to siblings. This leaves the agent without critical context for invocation.

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% with clear parameter descriptions. The description adds value by listing supported operators (&&, ||, !, ^, =>, <=>) which are not in the schema, enhancing understanding of the expression syntax.

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 evaluates a boolean logic expression given a variable assignment map, listing supported operators. This directly distinguishes it from siblings like generate_truth_table (which enumerates assignments) and solve_sat (which checks satisfiability).

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 usage for evaluating expressions with specific operators, but does not explicitly state when to use this tool versus alternatives (e.g., evaluate_json_logic, evaluate_decision_table). No when-not-to-use guidance is provided.

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