denoise_image

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

No annotations are supplied, so the description carries the full behavioral burden. It does disclose a Returns dictionary with denoising results and documents model_type options, but it never states side effects: whether output_path is auto-generated when omitted, whether the input file is ever overwritten, or whether on-disk model weights must be downloaded on first run.

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?

Docstring format with a one-line purpose leading, followed by a compact args table and a short Returns section. Each element earns its place with no redundancy, though some glosses (e.g., 'channel specification') could be tightened without losing value.

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 6-parameter, 0% schema-coverage tool, the description covers purpose, every parameter, and the return value shape. Since an output schema exists, spelling out the exact dictionary keys is unnecessary. Remaining gaps are runtime behaviors (auto-save behavior, model downloads), which an agent cannot infer.

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?

With 0% schema description coverage, the description compensates by enumerating all six parameters with meaningful glosses—model_type even lists concrete choices (denoise_cyto2, denoise_cyto3). A few entries remain vague ('channels: Channel specification', 'diameter: Expected object diameter for scaling'), leaving exact formatting to the schema.

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 the exact operation (denoise), the resource (microscopy image), and the method (Cellpose restoration models) in the opening line. This immediately distinguishes it from siblings like deblur_image, upsample_image, and the segment_cells_* family, which perform different operations.

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?

Never states when to prefer denoising over the sibling restoration tools (deblur_image, upsample_image) or lists any alternatives. No exclusions, prerequisites, or selection criteria are given—usage is only implied by the tool's own name.

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