image_quantize

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

No annotations are provided, but the description discloses key behaviors: it returns a stats object and preview image, details dithering options, explains the 'corrected' parameter's effect on preview while noting reporting is unaffected, and mentions 2× upscaling for small images. This gives the agent a clear picture of what will happen.

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 a compact docstring with explicit Args and Returns sections. It front-loads the main purpose in the first sentence and uses no filler. Every sentence adds value, from parameter semantics to return details.

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?

With no output schema and no annotations, the description must convey all relevant context. It covers inputs, outputs, defaults, and edge-case behavior (upscale, corrected preview). It does not mention error conditions, but for this tool's complexity, the description is sufficiently complete for an agent to invoke it correctly.

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?

The input schema only provides types and defaults. The description compensates fully by explaining each parameter: 'source' accepts a filesystem path, base64, or data URI; 'dither' lists three options with default; 'corrected' explains sunlight-corrected preview behavior. This adds significant meaning over the bare schema.

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 opens with a specific verb and resource: 'Quantize an image to the Pebble 64-color palette; return stats + preview.' This clearly distinguishes from sibling tools like color_nearest or image_prep by specifying the exact palette and output.

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 provides clear context for use: quantization of an image to a specific palette, with an input-format note for hosts without filesystems. However, it does not explicitly name alternative tools or exclusionary conditions, so it falls short of the highest bar.

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