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optimize_local_image

Convert local images to WebP with automatic EXIF rotation, resizing, and quality control to maintain consistent performance when replacing stock photos with client photos.

Instructions

Convert a local image file (e.g. a client-provided photo) to WebP with the same pipeline used by download_image: EXIF rotation, max-width resize, quality control. Use it when replacing stock photos with the client's real photos so performance stays consistent. Input must be a file inside the project directory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qualityNo
filenameNoOutput name without extension, kebab-case. Defaults to the source file name.
maxWidthNo
inputPathYesRelative path to the source image inside the project.
outputDirNoRelative directory inside the project to save the file.public/images
overwriteNo
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the conversion pipeline (EXIF rotation, resize, quality), which adds behavioral context. However, it does not mention potential side effects like overwrite behavior (default false), file size limits, or error handling, leaving some gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, each essential: defines function, gives usage context, states constraint. No fluff. Information is front-loaded and clear.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of output schema and annotations, the description covers purpose, usage, and input constraint. However, it omits details about return value (e.g., success/path), error conditions, and behavior of parameters like overwrite. This is adequate but leaves the agent needing to infer some behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50% (3 of 6 parameters have descriptions). The description adds context about the pipeline (quality, max-width) but does not elaborate on individual parameter semantics beyond what the schema already provides. Baseline 3 is appropriate; it doesn't significantly enhance parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it converts a local image to WebP using a specific pipeline (EXIF rotation, max-width resize, quality control). It distinguishes from siblings by mentioning the same pipeline as download_image and a specific use case (replacing stock photos).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit when-to-use guidance ('Use it when replacing stock photos...') and a key constraint ('Input must be a file inside the project directory'). This helps the agent decide context, though it doesn't explicitly mention when not to use it or contrast with search_images.

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

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