Skip to main content
Glama

faf_enhance

Polish project files by applying AI-driven enhancements with optional multi-model consensus and dry-run preview.

Instructions

Refine a project.faf with an AI model (claude/gemini/grok, optionally by consensus). Returns the enhanced content, or a dry-run preview when dryRun is set. Use this to polish after faf_auto and faf_go have filled the slots.

Input Schema

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

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

Annotations indicate readOnlyHint=false and destructiveHint=false, but description does not clarify whether changes are persisted or if it only returns the enhanced content. DryRun parameter hints at preview mode, but persistence is ambiguous. No output schema provided.

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

Conciseness5/5

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

Two sentences, front-loaded with action and parameters, concise and to the point without redundancy.

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

Completeness3/5

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

Covers purpose and usage timing, but lacks behavioral details (e.g., side effects) and has a model name discrepancy. Adequate but not comprehensive for a 5-parameter tool without output schema.

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

Parameters2/5

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

Schema coverage is 100%, but description contradicts schema by listing 'grok' instead of 'chatgpt' and omitting 'universal'. Description adds little beyond labeling consensus and dry-run, but the model discrepancy reduces reliability.

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

Purpose5/5

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

Clearly states the tool refines a project.faf using AI models (claude/gemini/grok, optionally by consensus). Distinguishes from siblings by positioning it as a polishing step after faf_auto and faf_go have filled slots.

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

Usage Guidelines4/5

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

Explicitly says to use after faf_auto and faf_go have filled slots, providing context. Could be improved by noting when not to use, but the guidance is clear.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Wolfe-Jam/claude-faf-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server