continuum_subtract_ha

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

No annotations are provided, so the description carries the full burden, and it does well: it discloses in-place mutation, the exact mathematical operation, 64-bit PixelMath execution, truncation to [0,1], and the reported median and max. It does not cover failure modes, but core behavior is clearly visible.

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?

Two dense sentences capture the operation, the exact formula, the processing mode, and the result reporting. There is no filler, and the action is front-loaded.

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 no annotations and no output schema, the description provides enough operational detail to invoke the tool: the in-place target, the source channel, the factor semantics, numeric clamping, and the reported outputs. It omits explicit error cases and alternative-selection guidance, but is otherwise complete.

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 100%, so the baseline is 3. The description reinforces the meaning of continuum_factor and the roles of ha_id and rgb_id through the formula, but adds little beyond what the schema already states.

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?

States a precise verb and resource: subtract the scaled R channel from an Ha view, in place. The explicit formula Ha = max(0, Ha - continuum_factor * R) makes the operation unambiguous and distinguishes it from related narrowband tools like ha_inject_red.

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 gives no guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. With a large sibling set containing similar narrowband operations, an agent gets no routing help beyond inferring from the formula.

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