Edit image with a prompt (Magic Prompt AI)

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

Annotations already declare the mutation profile (readOnlyHint=false, openWorldHint=true, non-idempotent, non-destructive). The description adds one genuinely useful operational fact not in annotations: cost of 1 credit per variation. Beyond that it says nothing about what is returned, whether the source image is preserved, or any permission requirements, which is thin for a paid generative call.

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?

Three dense sentences: capability plus examples first, then the reference-image mechanism, then the sibling escape hatch and billing note. Every clause carries information; the examples do real work in illustrating prompt style.

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 9-parameter generative tool with no output schema, the description covers the essential decision inputs: what to prompt, how references behave, when to use the sibling, and the cost model. It leaves engine/resolution/variation trade-offs and returned artifact shape unexplained, but the core call path is complete.

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%, so all nine parameters including enum constraints are already documented structurally; the baseline of 3 applies. The description adds only the semantic intent of reference_images (products, materials, mood boards to place or apply), which the schema already mostly conveys, plus no guidance on engine, resolution, or variations.

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?

States a specific verb+resource ("edit any image") and anchors it with three concrete instruction examples, so the agent knows exactly what kind of input it accepts. It also distinguishes itself from the closest sibling by naming luw_magic_wand and the condition that selects it.

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?

Gives a clear usage context (plain-language edits, reference images for placing products/materials/mood boards) and an explicit alternative for one case: area-restricted edits go to luw_magic_wand. It stops short of routing among the other image siblings (luw_generate_image, luw_interior_design, luw_render), so it is strong but not exhaustive.

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