Text to image (Fluw AI)

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

Annotations cover the safety profile (not read-only, open-world, non-idempotent, non-destructive), so the burden is lighter. The description still adds genuinely useful operational context the annotations lack: a per-image cost of 2 credits and the fact that format="svg" reroutes execution to a different underlying model.

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 dense sentence plus a short cost/format clause; the core capability is front-loaded and nothing is wasted. It is slightly overstuffed with use-case examples, but each clause carries information.

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 creative generation tool with no output schema, the description covers purpose, cost, and the vector mode but omits how results are delivered — notably whether generation is asynchronous and requires luw_get_result, and how multiple variations are returned. That omission matters given the sibling luw_get_result exists.

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 89%, so the schema already documents seed, image, engine, format, styles, variations, and enhance_prompt. The description restates the guide-image option and the svg/vector-model behavior, which the schema also covers, adding little beyond it. Baseline 3 is appropriate when the schema does the heavy lifting.

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 ('generate a photorealistic image or illustration from a text prompt') and enumerates use cases, so the agent knows exactly what it produces. It partially differentiates from siblings by naming the Fluw Vector AI switch for format="svg", but does not explicitly distinguish itself from luw_generate_pattern, luw_render, or luw_vectorize_image.

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?

Usage is implied by the prompt-driven framing and the optional guide-image note, and the svg tip gives one actionable routing hint. However, there is no explicit when-to-use vs. when-not guidance against the many neighboring generation tools (luw_render, luw_edit_image, luw_generate_pattern).

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