photographi-mcp

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

With no annotations provided, the description carries full burden. It discloses the return format ('list of hex color codes') and default behavior ('Default is 5 colors'), but lacks details on error handling, performance characteristics, or image format requirements.

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?

Three sentences with zero waste: first states purpose and method, second specifies output format, third provides usage context. Each sentence earns its place and is front-loaded with essential 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?

Given the tool's moderate complexity, no annotations, but with output schema present, the description covers core functionality well but could benefit from more behavioral context about limitations or prerequisites for the image processing.

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 50% (only image_path has description), but the description compensates by explaining the 'colors' parameter's purpose ('representative color palette'), default value ('Default is 5 colors'), and output format context, adding meaningful semantics beyond 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 clearly states the specific action ('Extracts a representative color palette'), resource ('from a single image'), and method ('using K-Means clustering'), distinguishing it from siblings like photographi_get_folder_palettes (multiple images) or photographi_analyze_photo (general analysis).

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 when to use ('for design inspiration or color grading reference') and implies usage for single images, but doesn't explicitly state when not to use or name alternatives like photographi_get_folder_palettes for multiple images.

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