edit_image

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

The description says the result is written to disk as a PNG and the source file is never modified, which are useful behavioral details. However, with no annotations provided, the description carries full burden. It does not disclose if the operation is reversible, whether it requires any specific authentication or permissions, or any side effects (e.g., whether it overwrites existing output files silently). It mentions the output is a PNG even if the source is JPEG, which is valuable. Overall, it provides moderate transparency but lacks some important details.

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 very concise: three sentences covering purpose, output format, and behavioral assurance. No superfluous words. It is front-loaded with the core action and a clear summary. Each sentence adds distinct value.

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 the tool has three parameters (all with schema descriptions), no output schema, no annotations, and no nested objects, the description provides the essential context for an editing operation with output to disk. It explains the return value (path to the result) despite there being no output schema. However, it does not specify if the prompt can be a plain text instruction or requires specific formatting, nor does it list supported edit capabilities (e.g., only simple changes? complex edits?). For a tool with no annotations, this leaves some gaps in completeness.

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% (all three parameters have descriptions in the schema), so the baseline is 3. The tool description adds value beyond the schema by confirming that 'image' must be a path to a PNG or JPEG, 'prompt' is a text instruction for editing, and 'output_path' must end with '.png'. The description contextually reinforces the parameter meanings, helping the agent understand their roles beyond the schema's property descriptions.

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 that this tool edits existing PNG or JPEG images using gpt-image-2 on Azure AI Foundry, following a text instruction. It also specifies that the result is saved to disk as a PNG and the source file is never modified. This provides a specific verb (edit), resource (PNG/JPEG image), and distinct operation (following a text prompt). It distinguishes edit from the sibling generate_image (which likely creates new images instead of editing existing ones).

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 mentions the supported image formats (PNG, JPEG) and that the source file remains unchanged, but it does not provide explicit guidance on when to use this tool versus the sibling tools check_config or generate_image. There is no 'when to use' or 'when not to use' advice, and no mention of prerequisites (e.g., image must exist, must be a supported format). The agent is left to infer usage context from the tool name and input schema.

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