implement_from_image

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

With no annotations, the description discloses a key behavioral trait—it delegates to a CLI worker rather than operating directly. However, it does not mention side effects, permissions, reversibility, or response behavior, leaving important gaps for a tool that likely modifies code.

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 short sentences, front-loaded with the core purpose, then the mechanism and use cases. Every sentence earns its place without redundancy or filler.

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?

The description covers purpose, mechanism, and concrete use cases, which is sufficient for a tool with three well-documented parameters. However, it omits any mention of return behavior or error handling, which would be valuable given the lack of an output schema.

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%, so the baseline is 3. The description does not add any parameter-specific meaning beyond what the schema already states; for example, the 'description' parameter is described identically in both places.

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?

Clearly states the verb ('Build or fix code') and the resource ('based on an image'). Explains the mechanism (Chat describes image, tool sends description to CLI worker) and distinguishes it from analysis-focused siblings like analyze_image by emphasizing implementation.

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?

Provides explicit use cases: 'screenshots of bugs to fix, mockups to build, error messages to resolve.' This gives clear context for when to use the tool, but it does not mention alternatives or when not to use it, so it stops short of a 5.

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