plan_ui_fixes

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

With no annotations, the description fully carries the burden. It states 'This tool never modifies source files' and details the return structure, ensuring the agent understands the tool's safety and output.

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 paragraphs with no wasted words. First paragraph explains purpose and return, second gives usage guidance. Efficient front-loading of key 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?

No output schema, but the description details the return type and structure. Two parameters with defaults are covered. Adequate for a planning tool that generates patch suggestions.

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 coverage is 100%, so baseline 3. The description does not add semantics beyond the schema's parameter descriptions for 'target' and 'maxFiles', which are self-explanatory.

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 builds a dry-run UI fix plan from diagnosis evidence and app graph data, and specifies the return structure with patches, summary, and caveats. This distinguishes it from sibling tools like diagnose_app_quality.

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 explicitly says 'Use this tool: to decide what a human or coding agent should patch before calling memi fix apply or making manual edits,' providing clear usage context. It lacks explicit when-not to use, but the dry-run nature implies it.

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