image_statistics

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

Annotations already provide readOnlyHint=true and destructiveHint=false, and the description repeats 'Read-only' without adding much beyond that. It adds some context by framing the tool as a post-processing check, but it does not disclose new behavioral traits like side effects, rate limits, or data dependencies.

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 compact and front-loads the metric list, which is the core value. The 'Read-only' phrase is redundant with annotations but harmless; overall every sentence contributes.

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?

The description lists the expected output metrics, which is helpful since there is no output schema, but it does not explain how the 'id' parameter selects the image or that 'rect' restricts the region. For a tool with four parameters and rich output, this is adequate but not fully 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 coverage is 75% with direct descriptions for rect, clip_low, and clip_high; the remaining id parameter lacks schema guidance and is not clarified in the description. The description's mention of clipped and saturated counts loosely relates to clip thresholds, but it does not explain parameter meaning beyond 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?

The description clearly identifies the tool as computing per-channel statistics (median, MAD, mean, σ, min/max, clipped counts, noise estimate, etc.), which makes the purpose obvious. It does not name a sibling tool explicitly, but the metric list differentiates it from tools like histogram or measure_stars.

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 explicit usage context with 'Use after every stretch/sharpen step,' which tells agents when to call it. It does not name alternatives or state when not to use it, but the timing guidance is clear and operational.

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