faf_enhance

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

Without annotations, the description must disclose behavioral traits. It states 'Enhance .faf with AI optimization' but does not explain whether the tool modifies the file in-place, requires network access for AI models, or has destructive potential. The existence of a 'dryRun' parameter hints at a preview feature, but the description does not clarify that changes are permanent by default.

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 single, concise sentence that efficiently conveys the core action. However, it is under-specified for the tool's complexity; brevity here comes at the cost of missing critical details like behavior and usage context.

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 absence of an output schema and annotations, the description should provide a complete picture of what the tool does, its side effects, and when to use it. It fails to mention return values, whether the .faf file is required to exist, or the nature of 'AI optimization' (e.g., improving prompt quality vs. converting format). The tool has four optional parameters, indicating multiple modes, yet the description ignores this complexity.

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 provides full descriptions for all four parameters (100% coverage), so the description adds little extra meaning. It does not give examples or clarify relationships between parameters (e.g., 'consensus' and 'model'). Baseline 3 is appropriate since the schema already does most of the work.

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 action ('Enhance') and the resource ('.faf') with a specific intent ('AI optimization'). It differentiates from siblings like faf_read (read-only) and faf_write (general write) by focusing on improvement using AI. However, it lacks specificity about what 'enhance' entails (e.g., formatting, content generation).

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?

No explicit guidance on when to use this tool versus alternatives like faf_write (direct writing) or faf_friday (specific enhancement). The description does not mention use cases, prerequisites, or situations where this tool is preferred. The agent must infer usage from the tool name alone.

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