Controlled disorder grid

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

The description adds significant behavioral context beyond annotations: it reveals that the tool creates a baseCOMP, exposes live controls, returns a summary with JSON and preview, and ensures stability via hashing. Annotations only indicate readOnlyHint=false, openWorldHint=true, destructiveHint=false; the description fully covers the creation side effect and reproducibility. No contradiction.

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 a single, dense sentence that conveys all key information without wasted words. It front-loads the core concept and then details the output. While slightly verbose, it remains efficient. Could be improved with line breaks for readability, but the content earns its place.

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?

Given 14 parameters, full schema coverage, no output schema, and minimal annotations, the description is sufficiently complete. It explains the output (baseCOMP, controls, return format) and the core algorithm (hashing, stable chaos). It does not detail every possible interaction but covers the essential workflow for an AI agent to select and use the tool.

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 100%, so baseline is 3. The description adds context about the disorder knob scaling multiple jitters together and the outline giving a Schotter look, but these are also hinted at in parameter descriptions. It doesn't add much meaning beyond what the schema provides for each parameter, but it does tie them together into a coherent operation.

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 precisely states the tool's function: generating a grid of quads/cells with a single disorder knob controlling position, rotation, and scale jitter. It clearly identifies the resource (grid), the action (generate), and the key parameter, making it distinct from sibling tools which are mostly about other types of creation or effects.

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 implies usage in generative design contexts (mentioning Schotter study) but does not explicitly state when to use this tool over alternatives. It lacks guidance on when not to use it or what conditions are ideal. With many sibling create_* tools, more explicit differentiation would help.

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