MindFluence
starsforks
How to install MindFluence?
madeval/mindfluence
$git clone https://github.com/MADEVAL/MindFluenceREADME.md
| 1 | # MindFluence |
| 2 | |
| 3 | []() |
| 4 | [](LICENSE) |
| 5 | []() |
| 6 | |
| 7 | [ **English** | [Русский](README.ru.md) ] |
| 8 | |
| 9 | > **Persuasion engineered through psychology, not manipulation.** |
| 10 | |
| 11 | An AI prompt-skill that turns 20 cognitive biases into high-converting marketing copy - for any language, any platform, any audience. **v2.2: self-contained single-file with narrative depth.** All tables, 13 anti-patterns with detection rules, cultural data, and few-shot examples are inlined into SKILL.md. Named Person Story Arc (NPSA) requirement ensures human-quality output alongside mechanical verification. No external file reads required for core operation. |
| 12 | |
| 13 | --- |
| 14 | |
| 15 | ## What is this? |
| 16 | |
| 17 | **MindFluence** is a system prompt (skill) for LLMs - GPT, Claude, Gemini, DeepSeek or any capable model. It transforms the AI into a marketing strategist who understands *why* humans click, read, and buy - not just *what* to write. |
| 18 | |
| 19 | It's built on decades of research in behavioral economics and evolutionary psychology: Kahneman's two systems, Cialdini's principles, Munger's psychological misjudgments, Festinger's cognitive dissonance - distilled into actionable copywriting instructions. |
| 20 | |
| 21 | ## How it works |
| 22 | |
| 23 | 1. **Load `SKILL.md`** as a system prompt into any LLM. That's it - the file is fully self-contained. |
| 24 | 2. **Give a task:** "Write a LinkedIn post about..." / "Create a landing page for..." / "Audit this ad for cognitive biases." |
| 25 | 3. **Get output** with every bias labeled, every decision explained, every word psychologically justified. |
| 26 | |
| 27 | **The LLM uses a single-table Bias Selection Router** (audience × product × platform → instant bias stack) instead of a 10-step procedure. After generating, it runs a **mechanical Post-Generation Verification** - 6 checks (numbers, names, exit, explain, blame-system, human narrative) - and a mandatory **Named Person Story Arc** requirement before delivering. |
| 28 | |
| 29 | **Four modes:** |
| 30 | - **Quick Mode** (default) - 3-step internal procedure: lookup router → scenario override → verify. Fast for user, fast for LLM. |
| 31 | - **Deep Mode** - the AI asks 5 clarifying questions at once, then routes through the same lookup. |
| 32 | - **Audit Mode** - analyzes existing copy for biases and anti-patterns using mechanical detection rules (13 anti-patterns including Statistical-Only Fallacy). |
| 33 | - **Optimize Mode** - iterates on underperforming copy using funnel-to-bias mapping. Generates A/B variants with statistical confidence thresholds. Also handles qualitative rewrites without metrics: tone shifts, bias injection/removal, anti-pattern fixes, audience/platform adaptation (7 rewrite intents). |
| 34 | |
| 35 | ## The 20 Cognitive Biases |
| 36 | |
| 37 | | # | Bias | Category | Marketing Use | |
| 38 | |---|------|----------|---------------| |
| 39 | | 1 | **Social Proof / Bandwagon** | Social | Used by teams at Google, Airbnb, and 10,000+ startups | |
| 40 | | 2 | **Anchoring** | Optimizer | Enterprise: $499/mo → Pro: $99/mo | |
| 41 | | 3 | **Framing** | Filter | "90% success rate" vs "Only 10% fail" | |
| 42 | | 4 | **Appeal to Authority** | Social | The same method taught at Harvard Business School | |
| 43 | | 5 | **Fear / Loss Aversion** | Filter + Social | Every day without X costs you $200 in missed revenue | |
| 44 | | 6 | **Availability Heuristic** | Optimizer | "Sarah tripled her revenue in 3 months. Here's the exact playbook." | |
| 45 | | 7 | **Confirmation Bias** | Filter | "You already know newsletters are broken. Here's the data that proves your instinct right." | |
| 46 | | 8 | **Cognitive Dissonance** | Filter + Optimizer | "You care about health but skip breakfast. Our 2-minute shake fixes the gap." | |
| 47 | | 9 | **Survivorship Bias** | Optimizer | "The 23% who succeeded all followed this pattern. The 77% did not." | |
| 48 | | 10 | |
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