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

The description adds important behaviors beyond annotations: async execution, polling requirement, and a $0.03 charge. Annotations only say readOnlyHint=false and openWorldHint=true, so the description carries the load and does so clearly. It does not cover failure modes or data retention, but it covers the core workflow.

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 tight sentences: the first states purpose and price; the second explains the async workflow. This is appropriately front-loaded and has no fluff.

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 one-parameter async tool, the description covers the essential steps: submit image, receive generation_id, poll get_generation. Cost and input format are included, and no output schema exists to explain. It could mention error handling, but it is otherwise 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?

The schema already fully documents the single 'image' parameter with 100% coverage, including accepted formats (URL or data URI). The description adds no new parameter-level semantics, so the baseline of 3 applies.

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 tool's function: 'Colorize black & white photos' with a specific verb and resource. It implicitly distinguishes from the sibling ai_video_colorizer by limiting scope to photos, and the title reinforces this. No ambiguity about what task it performs.

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 gives concrete invocation guidance: it is asynchronous, returns a generation_id, and instructs the user to call get_generation until status is 'completed'. It also mentions cost per photo, which helps decide whether to use it. It does not explicitly name alternatives or exclusion criteria, but the photo-specific scope provides enough context.

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