transform_image

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It discloses one genuinely useful behavior: file paths are auto-processed without dumping the base64 string into the conversation. But it does not disclose cost implications of an AI generation call, whether the original image is preserved, latency expectations, or whether upstream preparation (e.g., prepare_image) is needed.

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?

Two sentences with no filler. The core purpose is front-loaded in the first sentence, and the second sentence carries a concrete, actionable behavioral detail. Every clause 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?

For a 9-parameter, 2-required tool with no annotations and no output schema, the description covers input handling but leaves gaps: no guidance on how transform_image relates to the prepare_image workflow among siblings, no cost expectations, and no output-behavior detail beyond what the schema's display_mode enum already provides. Adequate but not 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%, establishing the baseline of 3 even with no param info in the description. The description reinforces the image parameter's accepted formats (path/URL/base64) and adds the 'without displaying the base64 string' behavioral nuance, but adds nothing about prompt, strength, model, or control_type beyond what the schema already documents.

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 ('Transform'), resource ('existing images'), and mechanism ('using AI with various control methods'). This clearly distinguishes it from generate_image (creates new images), enhance_image (implies improvement rather than arbitrary transformation), and prepare_image/read_local_image (image I/O utilities). An agent can tell which tool to reach for without inspecting the schema.

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 context is implied — use this when an existing image needs modification rather than generation — and the input-format note gives practical guidance on what it accepts. However, no explicit when/when-not conditions or alternatives are named, and the closest sibling (enhance_image) is never referenced, leaving the selection decision between transform and enhance to inference.

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