raster_adjust

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

With no annotations, the description carries the full burden for behavioral disclosure. It provides critical scaling semantics (1.0 = no change, >1.0 = increase, <1.0 = decrease), which is helpful for numeric parameters. However, it does not disclose whether the original file is modified in place, whether an output path is required, or any side effects. This is a significant gap for a mutating tool.

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 two sentences, succinct, and front-loaded with the purpose. The scaling rule is efficient and earns its place. No redundant information.

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 tool with 7 parameters, no output schema, and no annotations, the description is incomplete. It explains the value scaling but does not cover critical context: whether at least one property must be set, behavior if no numeric params are given, file handling (in-place vs output), or validation ranges. An agent would need to infer or experiment to use it safely.

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 adds a universal rule for all numeric parameters (gamma, contrast, etc.) that explains the value meaning, which the schema does not. However, it does not explain the 'path' or 'output' parameters, leaving their roles to inference. The blanket rule is useful but not per-parameter.

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 the tool's action ('Adjust image properties') and the resource type (image properties), which distinguishes it from sibling tools like raster_convert, raster_resize, and raster_crop that perform geometric/format transformations. However, it does not explicitly list which properties are adjustable, relying on the schema to convey that.

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?

No guidance is provided on when to use raster_adjust versus alternatives like raster_filter or raster_enhance. The sibling tool list suggests related operations, but the description offers no exclusions, prerequisites, or contextual cues for selection.

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