measure_core_clipping

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

With no annotations, the description carries full responsibility for behavioral disclosure. It thoroughly explains the algorithm: how the brightest block is found, how boxes are sampled (every 2nd pixel vs every pixel), that boxes are centered and clamped to the image, and the exact output fields including the luminance formula. It does not explicitly state it is read-only, but the measurement nature and lack of mutation verbs make this clear.

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 and information-rich, with every sentence serving a purpose: defining the measurement, specifying the algorithm, and listing return values. It is not overly verbose, but the technical detail makes it slightly longer than the minimum; still well-organized and front-loaded with the core purpose.

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 measurement tool with only two parameters and no output schema, the description is complete: it defines the sampling strategy, the exact return fields, and the luminance formula. An agent can invoke it correctly without additional information, making it self-sufficient.

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%: both level and view_id have descriptive comments. The description adds the luminance formula and algorithmic context but does not materially extend the parameter meanings beyond what the schema already states. Baseline 3 is appropriate as the schema already carries the semantic load.

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 states a specific verb and resource: it measures how much of the brightest region exceeds a given level, with precise algorithmic details (64px block, 128px and 32px boxes, sampling pattern). This distinguishes it from sibling measurement tools like measure_clipped_blocks or measure_highlight_texture, which target different phenomena.

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 provides clear context for what the tool measures but does not explicitly compare it to alternatives or state when not to use it. It implies usage for clipping analysis in the brightest region, but an agent would need to infer selection from the tool name and description rather than explicit routing guidance.

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