kia_start_climate

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

The description goes far beyond annotations, disclosing the nested `climate.airCtrl` field, EV-specific `engine`/`ign3` behavior, separation of `commandAccepted` vs `stateConfirmed`, observed 30–60s delay, and the unconfirmed temperature behavior. It also reveals that seat/steering heating is deliberately not sent. This is rich, high-value 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 long but every sentence earns its place: it front-loads the core purpose, then packs essential caveats (dry-run, nested fields, EV behavior, timing, temperature unreliability, omitted heating) without redundancy. The structure is logical and information-dense.

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 (6 params, nested response semantics, no output schema), the description is remarkably complete. It explains success criteria (`climate.airCtrl` true), distinguishes request acceptance from state confirmation, warns about timing, and documents the lack of temperature/certain accessory support. This covers the likely failure modes and user expectations.

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%, but the description adds crucial semantics beyond property descriptions: it explains `confirm`'s dry-run vs real execution, `temperature` is best-effort and may be overridden by the car, `waitSeconds` reflects observed timing, and `durationMinutes` controls ignition duration. This meaningfully improves parameter understanding.

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 opens with a specific verb and resource: 'Start remote climate control / preconditioning (Kia `rems/start`, live-verified).' This clearly states what the tool does and distinguishes it from sibling tools like kia_stop_climate by naming the API operation.

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 explains the critical usage distinction between dry-run (without confirm:true) and actual execution (with confirm:true), and warns about temperature best-effort and omitted seat heating. It does not explicitly name alternative tools for exclusion (e.g., 'use kia_stop_climate to stop'), but the context is clear and sufficient for selecting this tool.

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