daylight_factor

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

With no annotations, the description carries the full burden. It discloses that the overcast sky is added internally, that it returns df_per_point plus summary metrics and e_outdoor, and that it can return a command plan when run=false. It also explains the scene_sets structure. This is substantial behavioral context, though it does not mention side effects like file writes or computational cost.

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 paragraph with a formula and a bullet-like explanation of key inputs and outputs. It is reasonably concise and front-loaded with the definition. However, the bullet for scene_sets and points could be tighter, and the mention of 'command plan' is slightly cryptic.

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 high parameter count (11) and no annotations, the description is not complete. It explains the core inputs (scene_sets, points, sensor_set) and the output format, but omits explanation for the other 7 parameters. Even with an output schema, the tool is too complex to rely on defaults without explanation.

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 compensate. It explains scene_sets, points, sensor_set, and run (implicitly), but leaves many parameters (day, hour, month, quality, gnd_refl, work_dir, rad_params) unexplained. The agent must guess their meaning from the schema or defaults, which is inadequate for a tool with 11 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 computes Daylight Factor per point under the CIE Standard Overcast Sky, with a formula. It is specific about the resource (daylight factor) and scope (per point, overcast sky). However, it does not explicitly distinguish it from sibling tools like annual_daylight or lm83_daylight, though the mention of 'gensky -c' hints at a specific static sky model.

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 does not provide any guidance on when to use this tool versus alternatives. It does not mention conditions, exclusions, or prerequisites. An agent would have to infer the appropriate use case from the metric definition alone.

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