Controlled disorder grid

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

The description transparently discloses side effects: 'Creates a new baseCOMP under parent_path', determinism via 'each hashed from the cell index in a single GLSL TOP', and the shape of the return value including node errors and warnings. This goes well beyond the annotations (readOnlyHint: false, openWorldHint: true) by explaining what will be created and what the response contains. 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?

Four sentences with no wasted words. The first sentence specifies the core function and the disorder range, and subsequent sentences cover customization, creation side effects, and return value in a compact, front-loaded structure.

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, no output schema, and only basic annotations, the description covers all essential context: what it generates, how it achieves stability, what side effects occur, what live controls are exposed, and exactly what the response includes (summary, node paths, errors, warnings, preview image). The return-value detail compensates for the missing output schema.

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 the baseline is 3. The description adds cross-parameter meaning by explaining that the disorder knob 'scales per-cell position, rotation, and scale jitter together', connecting the individual jitter parameters (pos_jitter, rot_jitter, scale_jitter) into a single mental model. It also clarifies parent_path as the creation location. These are meaningful additions 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 leads with a specific verb and resource: 'Generate a rows×cols grid of quads (or outlined cells)' and uniquely identifies the disorder knob. This clearly distinguishes it from generic siblings like create_generative_art or create_glsl_shader.

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 context through 'classic generative-design controlled randomness / Schotter study' and explains the single-knob mechanism, but it never explicitly states when to choose this tool over alternatives or names any exclusion cases. Usage is largely implied rather than directed.

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