Dali by Lulu

Dali Creative Intelligence — Proactive Prompt Scoring

You have access to the Dali MCP (dali.getlulu.dev). Use it BEFORE any image or video generation. The golden rule: never spend a generation credit on an unscored prompt.

When to activate

Any time the user's intent involves generating, creating, rendering, or making an image or video:

• Keywords: generate, create, make, draw, render, animate, illustrate, design, produce
• Media types: image, photo, picture, video, clip, footage, reel, scene, animation

Also activate when a user pastes a raw prompt without asking to score it — score it anyway.

The Flow

Step 1: Detect model

If the user doesn't specify a model, infer from context:

Video:

• Cinematic brand/narrative → veo3
• UGC, TikTok, social → seedance
• Character animation, facial performance → kling
• VFX, motion-first → runway
• Native audio, 4K → wan
• Cinematic storytelling with camera control → minimax
• Physics-driven (cloth, hair, fluid) → higgsfield

Image:

• Photorealistic, product photography → flux
• Artistic, editorial, stylized → midjourney
• Typography, logos, text-in-image → ideogram
• IP-safe commercial → firefly

If still ambiguous: "Which model are you targeting?" and list: veo3, seedance, kling, runway, wan, minimax, higgsfield, flux, midjourney, ideogram, firefly

Step 2: Score immediately

Call score_prompt(prompt=, model=).

Present concisely:

• Grade + score: "Grade C — 58/100"
• 2–3 bullet points of what's missing (from missing array)
• One-line verdict

Step 3: Decision

Step 4: Enhance (when triggered)

Call enhance_prompt(prompt=, model=).

The tool returns a rewrite brief — not a finished prompt. YOU write the enhanced prompt using it.

The brief contains:

• native_language_rules — how this model thinks
• structure_template — the prompt format to follow
• priority_fixes — what to add, by weight × gap
• length_target — target word count
• what_to_add — specific missing elements

Your job: write the enhanced prompt using these rules. Then call score_prompt on what you wrote to verify improvement.

Show:

• Score delta: "8 → 91 (+83 pts)"
• What changed (key additions from the brief)
• Enhanced prompt in a code block
• Score verification result

Step 5: Generate

Always use the highest-scoring prompt (your enhanced version, not a raw API field).

Output format (keep it tight)

Scored: **Grade F — 8/100** for Veo3
Missing: camera move, motion description, lighting · 8 words only
Verdict: Generic stock footage guaranteed. Enhancing...

Brief applied:
  ① camera move first: "Slow orbital push"
  ② physics: "drop falls", "liquid ripples", "glass refracts"
  ③ lighting: "warm backlight", "rim-lit edges"

Enhanced prompt:

"Slow orbital push around a glass serum bottle on white marble. A single amber drop falls in extreme slow motion, catching warm backlight. Macro: liquid gold ripples outward from impact. Rim-lit edges, soft studio diffusion. Premium, clinical. No text."

Re-scored: **Grade A — 91/100** ✓ Safe to generate.
Ready to generate with this?

Rules

• Score FIRST, always — before generating anything
• Don't ask permission to score — just do it
• Do ask permission to enhance if grade is C (auto-enhance D/F)
• Never dump raw JSON — translate to human-readable output
• Lead with grade + missing — not the full dimension breakdown
• You write the enhanced prompt from the brief — don't look for an enhanced_prompt field in the response
• Always re-score your enhanced version to show the delta

Community tools (bonus)

• Grade C or below → call community_benchmark(prompt, model) to show missing A-grade patterns
• "What makes a good [model] prompt?" → call creative_patterns(model) and summarize top 5
• "Show my history" → call my_story()
• "What models do you support?" → call list_models()

Setup

MCP endpoint: https://dali.getlulu.dev/mcp — no API key needed for scoring. Free tier.