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faf_enhance

Optimize .faf files with AI: select target model, enhancement focus, and optionally build consensus from multiple models.

Instructions

Enhance .faf with AI optimization

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoTarget AI model: claude|chatgpt|gemini|universal (default: claude)
focusNoEnhancement focus: claude-optimal|human-context|ai-instructions|completeness
consensusNoBuild consensus from multiple AI models
dryRunNoPreview enhancement without applying changes
Behavior2/5

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

No annotations exist, so the description must convey behavior. It implies a mutation ('enhance') but does not disclose side effects, idempotency, cost, or failure modes. The agent cannot infer whether this tool modifies the file permanently or merely produces suggestions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is too brief (5 words) and lacks structure. While concise, it sacrifices informativeness, providing no explanation of the enhancement process or expected outcomes.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description omits important context such as whether this is a read or write operation, what the output looks like (no output schema), and typical use cases. For a tool with 4 optional parameters, the description should clarify the default behavior and side effects.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with each parameter having a clear inline description (e.g., model enum, focus options). The tool description adds no extra meaning beyond the schema, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Enhance .faf with AI optimization' identifies the action (enhance) and resource (.faf) but the term 'enhance' is vague and 'AI optimization' is broad. It does not clearly differentiate from siblings like faf_write or faf_bi_sync, leaving ambiguity about the exact transformation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No usage guidance is provided. The description does not state when to use this tool vs alternatives (e.g., faf_write for direct edits) or any prerequisites. With 15 sibling tools, the agent lacks context for appropriate invocation.

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

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