dynamic_narrowband_blend

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

With no annotations, the description fully carries the transparency burden and succeeds: it discloses that the target is modified in place, the mask is temporary and removed afterward, the computation runs in 64-bit PixelMath truncated to [0,1], and it reports median and channel maxima. This is exactly the kind of behavioral context an agent needs.

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 dense but every sentence earns its place: summary, explicit channel formulas, soft-clamp behavior, mask construction, mask removal, numeric precision, and output reporting. No filler, no redundancy, and the most important behavioral facts come first.

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 an 11-required-parameter tool with no annotations and no output schema, this description is remarkably complete. It fully specifies the algorithm, the mask lifecycle, the numeric domain, and the reported output values, leaving no critical ambiguity for an agent deciding whether and how to invoke it.

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?

Although schema coverage is 100%, the description significantly enriches parameter meaning by embedding each parameter in the actual equations (e.g., g_ha_fraction's role in the G term, rolloff as the fraction of excess kept, mask_blur as Gaussian sigma). This bridges the gap between telling an agent what a parameter is and how it behaves.

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 precise statement: 'Add Ha and OIII (mono views) to an RGB view in place, through a temporary luminance mask.' This names the specific operation, resources, and mechanism, and is clearly distinguishable from siblings like ha_inject_red or lrgb_combine.

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 detailed math and mask behavior make the intended use context unambiguous: this is the tool for a dynamic Ha+OIII blend into RGB with a luminance mask. However, it does not explicitly compare itself to alternatives (e.g., ha_inject_red, synthetic luminance) or state when not to use it, so it falls short of a 5.

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