shannon_hartley

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

With no annotations provided, the description carries full burden and does well by disclosing key behaviors: it explains the mathematical formula used, specifies that claims exceeding the Shannon limit are 'physical impossibility', and mentions the PhysicalViolationError return for invalid claims. It doesn't cover error handling for other cases or rate limits, but provides substantial behavioral context.

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 well-structured and front-loaded with the core purpose, followed by usage guidelines and parameter explanations. Every sentence earns its place by providing essential information without redundancy, making it efficient for an AI agent to parse.

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 mathematical nature, 4 parameters with 0% schema coverage, no annotations, but with an output schema mentioned, the description is complete. It explains the tool's purpose, usage, parameters, and even hints at output behavior (PhysicalViolationError), leaving the output schema to handle return value details.

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?

With 0% schema description coverage, the description fully compensates by explaining all parameters: bandwidth_hz ('Channel bandwidth in Hz'), snr_linear and snr_db (clarifying linear vs dB units and their mutual exclusivity), and claimed_throughput_bps ('Optional throughput claim to validate'). It adds crucial meaning beyond the bare 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's purpose with specific verbs ('Calculate Shannon-Hartley channel capacity', 'validate throughput claims') and distinguishes it from sibling tools like 'noise_floor' or 'rf_link_budget' by focusing on channel capacity calculations rather than noise analysis or link budgeting.

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 provides explicit guidance on when to use this tool through a bulleted list ('Calculate maximum achievable throughput', 'Validate whether a throughput claim is physically possible', etc.), clearly differentiating its use cases from potential alternatives without needing to name specific siblings.

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