sample_color

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

With no annotations, the description carries the full burden. It usefully discloses the return format (rgba and '#rrggbbaa'), substituting for the absent output schema, but says nothing about coordinate origin, out-of-bounds behaviour, or whether it is a read-only sampling operation.

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?

A single well-formed sentence with the resource and return format front-loaded. No wasted words, though it is arguably too terse given the undocumented coordinates.

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 three-parameter read tool with no annotations and no output schema, the description covers the return value but leaves coordinate semantics and the layer-override behaviour only partially explained. Adequate but with clear gaps.

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 only clarifies the optional layer parameter ('a single layer if given'); x and y remain undocumented as to coordinate origin, units, or valid ranges.

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 names a specific verb+resource (sample the colour of one pixel) and scopes it to the visible image or a named layer. It is distinguishable from siblings such as find_color and read_pixels, though it does not say so explicitly.

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 when-to-use or when-not-to-use guidance is given. The agent is left to infer whether read_pixels, find_color, analyze_image, or this tool is appropriate for a colour lookup.

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