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

Annotations already declare readOnlyHint=true and idempotentHint=true, so safety is covered. The description adds useful behavioral context by stating it 'returns the styled prompt stack' and instructs pairing with generate_image, exceeding the baseline set by annotations alone.

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 concise, front-loaded with the core purpose, and each sentence earns its place. It avoids redundancy and stays within three short sentences.

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 simple tool with two parameters and no output schema, the description adequately explains the purpose, camera choices, return type, and downstream usage with generate_image. It complements the schema and annotations effectively.

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 parameters are well documented. The description adds extra meaning by mapping the style enum to specific camera bodies (Canon R5 + 85mm f/1.2 vs Hasselblad H6D + 80mm), reinforcing the parameter semantics 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 states the tool's function: it applies a golden-hour rim-light editorial portrait style and returns a styled prompt stack. It distinguishes itself from sibling apply_* tools by specifying the unique 'magic hour portrait' aesthetic and camera options.

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 on usage: choose a camera and then pair the returned prompt stack with generate_image. It implies the workflow without explicitly excluding alternatives, fitting the 'clear context, no exclusions' level.

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