Free Prompt Transformer: Convert Any Prompt to 6 Nyquist Bands

What the Transformer Does

I built the sinc-LLM Prompt Transformer as a free online tool. It takes any raw prompt and breaks it into 6 specification bands. These bands follow the Nyquist-Shannon sampling theorem. The tool finds missing bands, suggests content for them, and produces a structured prompt that is 97% more token-efficient.

The tool is at sincllm.com. It is completely free. No account required.

How It Works

The transformer follows three steps.

Step 1: Band Detection

The tool reads your raw prompt. It finds which of the 6 bands are already there: PERSONA, CONTEXT, DATA, CONSTRAINTS, FORMAT, TASK.

Step 2: Gap Analysis

The tool finds missing bands. It scores the aliasing risk for each one. CONSTRAINTS (42.7% quality weight) and FORMAT (26.3%) are the highest priority when missing.

Step 3: Structured Output

The tool outputs a sinc JSON prompt with all 6 bands filled. You can send it to any LLM (ChatGPT, Claude, Gemini, open source models).

{
  "formula": "x(t) = ... sinc((t - nT) / T)",
  "T": "specification-axis",
  "fragments": [
    {"n": 0, "t": "PERSONA", "x": "..."},
    {"n": 1, "t": "CONTEXT", "x": "..."},
    {"n": 2, "t": "DATA", "x": "..."},
    {"n": 3, "t": "CONSTRAINTS", "x": "..."},
    {"n": 4, "t": "FORMAT", "x": "..."},
    {"n": 5, "t": "TASK", "x": "..."}
  ]
}

Before and After Examples

Input: Raw Prompt

"Write a marketing email for our new product."

Band coverage: 1/6 (TASK only). Aliasing risk: extreme. The model has to guess 5 missing bands.

Output: 6-Band Prompt

PERSONA: B2B SaaS email copywriter specializing in product launches
CONTEXT: [Fill: Company name, product type, target market, launch stage]
DATA: [Fill: Product name, key features, pricing, unique value proposition]
CONSTRAINTS:
- Maximum 200 words
- One clear CTA
- No superlatives or hype language
- Must include product name and pricing
- Professional tone, not salesy
- Compliance-safe (no unsubstantiated claims)
FORMAT: Subject line + greeting + 3 short paragraphs + CTA + signature
TASK: Write a cold outreach email announcing the product launch.

Band coverage: 6/6. Aliasing risk: near-zero.

Use Cases

• Prompt optimization: Paste any prompt to find and fill missing bands
• Cost reduction: Find noise tokens you can cut without losing quality
• Quality improvement: Make sure every prompt meets Nyquist rate before you run it
• Team standardization: Give your team a tool that keeps prompt structure consistent
• Education: Learn the 6-band framework by watching it work on real prompts

Try It Now

The transformer is live at sincllm.com. Paste any prompt and see the 6-band breakdown right away. No account, no cost, no data stored. No sign-up walls.

For programmatic access, use the CLI tool from the sinc-LLM GitHub repository:

py -X utf8 auto_scatter.py "your raw prompt" --execute

Or use the HTTP API:

POST http://localhost:8461/execute
Content-Type: application/json
{"prompt": "your raw prompt"}

Read my research paper for the theory behind the tool.

{
  "formula": "x(t) = Σ x(nT) · sinc((t - nT) / T)",
  "T": "specification-axis",
  "fragments": [
    {
      "n": 0,
      "t": "PERSONA",
      "x": "You are a Product manager for developer tools. You provide precise, evidence-based analysis with exact numbers and no hedging."
    },
    {
      "n": 1,
      "t": "CONTEXT",
      "x": "This analysis is part of a production system where accuracy determines revenue. The sinc-LLM framework identifies 6 specification bands with measured importance weights."
    },
    {
      "n": 2,
      "t": "DATA",
      "x": "Fragment importance: CONSTRAINTS=42.7%, FORMAT=26.3%, PERSONA=7.0%, CONTEXT=6.3%, DATA=3.8%, TASK=2.8%. SNR formula: 0.588 + 0.267 * G(Z1) * H(Z2) * R(Z3) * G(Z4). Production data: 275 observations, 51 agents."
    },
    {
      "n": 3,
      "t": "CONSTRAINTS",
      "x": "State facts directly. Never hedge with 'I think' or 'probably'. Use exact numbers for every claim. Do not suggest generic solutions. Every recommendation must be specific and verifiable. Include at least 3 MUST/NEVER rules specific to this task."
    },
    {
      "n": 4,
      "t": "FORMAT",
      "x": "Lead with the definitive answer. Use structured headers. Tables for comparisons. Numbered lists for sequences. Code blocks for implementations. No trailing summaries."
    },
    {
      "n": 5,
      "t": "TASK",
      "x": "Write the product announcement for sincllm.com/sinc-llm, a free browser-based prompt transformer"
    }
  ]
}