build_master_flat

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

Annotations only indicate non-read-only and non-destructive, so the description adds useful behavioral context: cached, async, and multiplicative EqualizeFluxes rejection normalization. It does not describe what artifact is produced or returned, but it goes beyond the annotation baseline.

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?

Three short sentences deliver the core operation, the critical warning, and the async/cached behavior with no filler. The information is front-loaded and every sentence earns its place.

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?

For a 7-parameter tool with no output schema and low schema coverage, this description is incomplete. It omits the meaning of wait despite being async, does not explain force or rejection, and does not clarify the files/group_id alternatives or what the tool returns.

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 only 29%, so the description must compensate, but it only clarifies the role of master_flat_dark and master_bias. It does not explain wait, force, rejection, or the relationship between files and group_id, leaving several parameters under-specified.

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 states a specific operation: calibrating flats using a master flat-dark or master bias, then integrating multiplicatively. This is clear enough to distinguish it from build_master_bias and build_master_dark, though it does not explicitly differentiate it from calibrate_lights.

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?

It gives clear input guidance: prefer a master flat-dark, fall back to a master bias, and never use the light master dark. It does not explicitly compare this tool to sibling calibration/integration tools, but the stated preference and hard negative are actionable.

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