Identify constant (closed form)

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

No annotations are provided, so the description must bear full burden. It discloses the algorithm (PSLQ + closed-form search), re-evaluation to 50+ digits, and honest 'UNIDENTIFIED' outcome, which is good behavioral transparency.

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?

Two sentences with no wasted words. First sentence clearly states purpose and methodology; second tells when to use and parameter details. Perfectly front-loaded and concise.

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 complexity and the presence of an output schema (not shown but indicated), the description covers algorithm, reliability, and parameters. It could mention output format, but output schema handles that. Overall complete.

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 description coverage is 100%, baseline 3. The description adds valuable context: 'value (decimal string — give MANY digits, >16)' and 'optional basis (constant names like ["pi","e"])', improving understanding beyond the schema.

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 identifies a real number's closed form using PSLQ and closed-form search, with independent re-evaluation. This distinguishes it from sibling tools like 'identify_sequence' and others.

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 explicitly says 'Use when you have a numeric constant and want to know what it IS.' While it doesn't list exclusions, the context makes usage clear.

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