/dm:eval-config

Purpose

Configure the evaluation system for a brand. Set minimum quality thresholds per dimension, adjust scoring weights based on industry priorities and content strategy, configure auto-reject thresholds that prevent substandard content from passing evaluation, and define content-type-specific quality standards that apply different bars to different formats.

The eval config determines how strictly content is scored and what the quality bar looks like for the brand. A healthcare company may weight hallucination risk and claim verification heavily while relaxing readability thresholds for technical audiences. A consumer brand may prioritize brand voice and readability while accepting lighter claim verification for awareness content. An agency managing multiple brands can set different configs per brand. This command makes those trade-offs explicit and adjustable rather than buried in defaults.

Input Required

The user must provide (or will be prompted for):

• Configuration action: What to do — view (show current settings), set-threshold (change a minimum score for a dimension), set-weights (change dimension weight distribution), set-auto-reject (change the composite score below which content automatically fails), set-content-type (configure content-type-specific overrides), recommend (get industry-appropriate settings suggestions), or reset (restore all settings to defaults)
• Dimension name (for set-threshold): The dimension to configure — content_quality, brand_voice, hallucination_risk, claim_verification, output_structure, readability, or composite
• Threshold value (for set-threshold): The minimum acceptable score (0-100) for the specified dimension. Content scoring below this threshold on any dimension is flagged as a failure on that dimension
• Weights (for set-weights): A JSON object mapping dimension names to their weights — e.g., {"content_quality": 0.25, "brand_voice": 0.20, "hallucination_risk": 0.20, "claim_verification": 0.15, "output_structure": 0.10, "readability": 0.10}. Weights must sum to approximately 1.0 (tolerance of +/- 0.02 for rounding)
• Auto-reject score (for set-auto-reject): The composite score below which content automatically fails regardless of individual dimension scores — typically 40-60 depending on brand standards
• Content type (for set-content-type): The content type to configure overrides for, plus the overrides themselves — custom thresholds or weights that apply only to that content type