garmin_run_conditions

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

No annotations exist, so the description bears full burden. It discloses the data sources (weather station actuals and watch temperature) and the correction algorithm. However, it does not explicitly state that the tool is read-only or describe error handling for invalid activity_ids. The behavioral traits are partially covered but not comprehensively.

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 moderately concise (four sentences) and front-loaded with a 'core' label. Every sentence contributes information about functionality, inputs, or rationale. Minor redundancy exists (e.g., explaining heat underestimation twice), but overall it is efficient and well-structured.

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 that an output schema exists (not shown), the description focuses on inputs and logic without needing to detail return values. It covers the key outputs, the optional target_pace behavior, and the data sources. It lacks mention of edge cases or data availability, but for a straightforward evaluation tool, the description is sufficient for an agent to understand and invoke it correctly.

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 0%, so the description must add meaning. It explains target_pace with an example and its role in completion judgment, adding semantic value. However, it does not explicitly map 'activity_id' to the tool's input or describe its type/usage, relying on the tool name and schema type. The explanation is helpful but not fully explicit for both parameters.

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 core purpose: combining a run with actual climate data for evaluation. It specifies outputs (actual pace, temperature/humidity, heat stress level, and equivalent pace under cool conditions) and explains the optional target_pace usage. This distinguishes it from siblings like get_activity_weather (raw weather) and weather_pace (general pace adjustment) by linking to a specific activity.

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 when to use the tool (e.g., to avoid underestimating effort on hot/humid days) but does not explicitly contrast with alternative tools such as get_activity_weather or weather_pace. It provides context for the correction logic but lacks direct 'when to use versus' guidance, leaving agents to infer appropriateness from the sibling list.

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