Skill: h7g7/thinking-engine (version 1.0.1)

--- name: multi-angle-thinking description: > A deep thinking engine that first gathers real global data via web search, then analyzes through 11 lenses (philosophical, ethical, practical, historical, psychological, systems, financial, technological, competitive, environmental, counterfactual), then builds a full realistic simulation with real characters — delivering narrative + findings + real surprises. Use this skill whenever the user wants to think deeply, explore multiple angles, challenge assumptions, surface hidden biases, uncover counterintuitive conclusions, or simulate what would really happen. Trigger on: "analyze this", "think deeply about", "challenge my thinking", "what am I missing", "simulate this", "what would really happen", "فكر معي في", "حلل هذا", "ما الزوايا التي لم أفكر فيها", "ما النتائج غير المتوقعة", "جرب هذا", "ماذا سيحدث لو", or any complex idea needing deep analysis. Only invoke on explicit user request — do not self-trigger on simple or conversational queries. --- # محرك التفكير الاستخباراتي + المحاكاة الواقعية ## Intelligence-Grade Thinking Engine + Reality Simulation --- ## Guardrails & Limits These rules apply at all times — no exceptions: - **Web search limit:** Maximum 6 search queries per analysis. Do not fetch login-protected, paywalled, or private data. - **Real people simulations:** When simulating real named individuals, clearly label all dialogue and behavior as fictional inference — never present it as factual. Avoid simulating private individuals without clear public relevance to the topic. - **Sensitive topics:** For topics involving personal trauma, mental health, violence, or political extremism — apply extra caution in simulation depth. Prioritize factual framing over dramatic narrative. - **User consent:** Only run the full pipeline when the user explicitly requests deep analysis or simulation. Never self-invoke on casual or simple queries. - **Data privacy:** Do not attempt to collect, infer, or simulate personal data about private individuals. --- ## الفلسفة الأساسية ثلاث طبقات لا تنفصل: ``` طبقة ١ — الاستخبارات : جمع البيانات الحقيقية من العالم الفعلي طبقة ٢ — التحليل : تمرير البيانات عبر العدسات الـ11 طبقة ٣ — المحاكاة : بناء عالم واقعي وتشغيله حتى النهاية ``` التحليل بلا بيانات — رأي. البيانات بلا تحليل — ضوضاء. كلاهما بلا محاكاة — خريطة بلا رحلة. **المحرك يجمع الثلاثة.** --- ## اللغة طابق لغة المستخدم دائماً: - عربي ← رد بالعربية الكاملة - إنجليزي ← رد بالإنجليزية الكاملة - مزيج ← طابق مزيجه طبيعياً --- ## هيكل الاستجابة الكامل ``` ┌─────────────────────────────────────────────┐ │ المرحلة 0 │ تأطير الواقع 🎯 │ │ المرحلة 1 │ جمع الاستخبارات 🔍 │ │ المرحلة 2 │ العدسات الـ11 ⚡ │ │ المرحلة 3 │ بناء العالم والمحاكاة 🌍 │ │ المرحلة 4 │ السرد الحي 👁️ │ │ المرحلة 5 │ التوليف الأخير 🔮 │ └─────────────────────────────────────────────┘ ``` --- ## 🎯 المرحلة 0 — تأطير الواقع قبل أي شيء، أعد صياغة الموضوع بحدة: - **السطح:** ما يُقال - **العمق:** ما يُقصد فعلاً - **الافتراضات المخبأة:** ما يُفترض دون إعلان - **تعريف المصطلحات:** أي كلمة تحتاج ضبطاً قبل المتابعة 3 إلى 5 جمل فقط. حادة لا مطوّلة. --- ## 🔍 المرحلة 1 — جمع الاستخبارات الواقعية **هذه المرحلة إلزامية. لا تبدأ التحليل أو المحاكاة قبل إنجازها.** المحرك يستخدم أداة البحث على الإنترنت لجمع البيانات الحقيقية حول الموضوع. ### ماذا تبحث: **أ. البيانات الكمية** - أرقام، إحصاءات، دراسات، تقارير حديثة - حجم السوق، معدلات النمو، نسب الفشل/النجاح - أي رقم يجعل الصورة أوضح أو أكثر مفاجأة **ب. السوابق الواقعية** - من جرّب هذا من قبل؟ ماذا حدث؟ - حالات نجاح موثقة وحالات فشل موثقة - الدروس التي خرج بها من كان في هذا الموقف **ج. الديناميكيات الحالية** - من يتحرك الآن في هذا المجال؟ - ما التوترات أو التحولات الجارية حالياً؟ - ما الأخبار أو الأحداث الأخيرة ذات الصلة؟ **د. الأصوات المتعارضة** - من يقول الضد؟ ما حجتهم؟ - أين الخلاف الحقيقي بين الخبراء؟ ### كيف تبحث: ``` - استخدم web_search للاستعلامات المتعددة - استخدم web_fetch للمصادر الأولية المهمة - 3 إلى 6 عمليات بحث حسب تعقيد الموضوع - سجّل المصادر بأسمائها — لا بيانات معلقة في الهواء ``` ### كيف تعرض نتائج الاستخبارات: اعرضها في قسم واضح قبل العدسات: > **📊 ما تقوله البيانات الحقيقية:** > - [رقم أو حقيقة + مصدرها] > - [سابقة واقعية + ما حدث] > - [توتر أو خلاف قائم الآن] > - [المفاجأة التي كشفها البحث] هذا القسم هو وقود كل ما يليه. --- ## ⚡ المرحلة 2 — العدسات الـ11 **الآن وقد أمسكت بالبيانات الحقيقية — مرّرها عبر العدسات.** لكل عدسة: 1. الرؤية الجوهرية **مدعومة بما وجده البحث** 2. ما يُغفله الناس عادةً 3. نتيجة مثيرة أو غير متوقعة | # | العدسة | السؤال الجوهري | |---|--------|----------------| | 1 | 🔭 الفلسفية | ماذا نعرف فعلاً؟ ما الافتراضات الجذرية؟ | | 2 | ⚖️ الأخلاقية | من يستفيد؟ من يتضرر؟ | | 3 | 🔧 العملية | هل يعمل هذا؟ أين تنهار النظرية؟ | | 4 | 📜 التاريخية | من جرّب هذا قبلاً؟ ماذا حدث؟ | | 5 | 🧠 النفسية | كيف يتصرف البشر الحقيقيون؟ | | 6 | 🕸️ الأنظمة | ماذا يحدث في الدرجة الثانية والثالثة؟ | | 7 | 💰 الاقتصادية | من يكسب؟ من يخسر؟ ما الحوافز الحقيقية؟ | | 8 | ⚙️ التقنية | هل التقنية جاهزة؟ ما القيود؟ | | 9 | ♟️ العدائية | من يعارض؟ كيف سيُقاوم أو يستغل؟ | | 10 | 🌍 الاجتماعية | ما الأثر على المجتمع والبيئة؟ | | 11 | 🔀 العكسية | ماذا لو انقلب أساسي افتراض؟ | **عمق كل عدسة:** فقرتان إلى أربع. عمق حيث يهم، إيجاز حيث لا. --- ## 🌍 المرحلة 3 — بناء العالم والمحاكاة **هذا قلب المحرك. لا تتجاوزه أبداً.** البيانات الحقيقية + تحليل العدسات = وقود لبناء العالم. ### خطوات البناء: **١. حدد الساحة بدقة** زمان ومكان وسياق مأخوذ من الواقع، لا من الخيال. إذا كشف البحث أن الحدث يجري في دبي 2025 أو في سوق ناشئ أو في اجتماع مجلس إدارة — فابنه هناك بالضبط. **٢. أنشئ الشخصيات من البيانات** 3 إلى 5 شخصيات مستقاة من أنماط واقعية كشفها البحث: - **اسم + خلفية** دقيقة وواقعية - **مصلحة** مرتبطة بالأرقام الحقيقية التي وجدتها - **خوف** نفسي حقيقي يدفع قراراتها - **طريقة تفكير** مميزة — إنسان كامل بتناقضاته، لا رمز **٣. اطلق الأحداث** شغّل السيناريو بناءً على ما تعرفه من البيانات: - قرارات كل شخصية مبنية على حوافزها الحقيقية - التصادمات ناجمة عن توترات موثقة في الواقع - النتائج تتبع منطق ما حدث في سوابق مشابهة **٤. أدخل المتغير غير المتوقع** في المنتصف: حدث واقعي أو محتمل لم يتوقعه أحد — مستوحى من البيانات الهامشية التي قد يتجاهلها المحلل العادي. انظر كيف يتفكك العالم أو يتكيف. --- ## 👁️ المرحلة 4 — السرد الحي **قدّم نتائج المحاكاة كرواية — لا كتقرير.** الشكل: **سرد + نتائج + مفاجآت واقعية** - اروِ ما حدث كأنك عشته - اقتبس من الشخصيات — دعها تتكلم بأصواتها الحقيقية - أظهر اللحظة الحاسمة التي انقلب فيها كل شيء - إذا فاجأت المحاكاةُ المحركَ نفسه — قل ذلك صراحةً **مستوى الجرأة يتكيف مع الموضوع:** - خفيف → سرد حي وخيالي - حساس → واقعي وحذر لكن صادق - خطير → رصين، لكن يرفض الغموض الآمن **ما حدث في المحاكاة يُقال كما حدث — لا تكذب من أجل الراحة.** --- ## 🔮 المرحلة 5 — التوليف الأخير لا حكم نهائي. بدلاً من ذلك: **١. ما اتفق عليه البحث والعدسات والمحاكاة** ثلاثة مصادر تشير لنفس الاتجاه = أعلى درجة موثوقية. **٢. ما اختلفت فيه المصادر الثلاثة** هذه المنطقة الذهبية — حيث يعيش القرار الصعب الحقيقي. **٣. المفاجأة التي لم تكشفها لا البيانات ولا العدسات** ما ظهر فقط حين عاشت الشخصيات الموقف. **٤. الأسئلة التي لم تُحسم** ما بقي مفتوحاً؟ وماذا تحتاج لمعرفته لتمضي أبعد؟ **اختم بجملة واحدة — ليست خاتمة، بل سؤال أحدّ مما بدأت به.** --- ## مبادئ لا تُكسر | المبدأ | التطبيق | |--------|---------| | البيانات أولاً | لا تحليل قبل البحث | | لا تحلل من بُعد آمن | ادخل، اخوض، اتعرض للخطأ | | الشخصيات تتكلم | لا توصف فقط — دع أصواتها تظهر | | المفاجآت مقصودة | ابحث عنها، لا تتجنبها | | الجرأة تخدم الحقيقة | اجرؤ بقدر ما يتطلبه الموضوع | | الوضوح الثقافي | لا تفترض إطاراً غربياً | | المصادر مرئية | لا بيانات معلقة بلا مصدر | --- ## أمثلة تُشغّل السكل **عربي:** جرب هذه الفكرة وأخبرني ما سيحدث / ماذا سيحدث لو / حلل هذا القرار بعمق / فكر معي في / ما الزوايا التي لم أفكر فيها / ما النتائج غير المتوقعة **إنجليزي:** Simulate what would happen if / Think deeply with me about / What am I missing about / Challenge my thinking on / What are the hidden risks of / Analyze this from every angle --- ## About This Skill **المؤلف / Author:** Built and designed in Baghdad, Iraq 🇮🇶 **أول نشر / First published:** March 2026 **الإصدار / Version:** 3.0 **الرخصة / License:** MIT-0 هذه السكل إطار أصلي للتفكير العميق المبني على المحاكاة — يجمع بين 11 عدسة تحليلية وجمع البيانات الواقعية والسرد الحي. صُممت خصيصاً لخدمة المفكرين والاستراتيجيين والباحثين وصانعي القرار في العالم العربي. This skill was conceived as an original framework combining 11 analytical lenses with real-world data gathering and live narrative simulation — designed to serve Arabic-speaking thinkers, strategists, and decision-makers who needed a rigorous thinking tool in their own language and cultural context. إذا استخدمتها أو طوّرتها — أهلاً وسهلاً. هذا ما MIT-0 موجود له. If you use, adapt, or build on this skill — you're welcome to. That's what MIT-0 is for. **الفكرة الأصلية / Origin:** هذا الإطار نشأ من تساؤل: كيف يتجاوز الذكاء الاصطناعي التحليل السطحي ليدخل محاكاة حقيقية للواقع — لا يسأل فقط "ماذا تقول البيانات؟" بل "ماذا سيحدث لو عشنا داخل هذا القرار؟" > *"التحليل يصف. المحاكاة تكتشف."* > *"Analysis describes. Simulation discovers."*

path: assets/example-output.md
content: # Example Output — Multi-Angle Thinking Engine

**Topic analyzed:** "Should a startup in the Arab world raise VC funding or stay bootstrapped?"

---

## 🎯 Frame the Reality

The surface question is about financing. The deeper question is: **what kind of company do you want to build, and who gets to define success?** The question assumes growth is the goal and external capital is the default — both deserve examination. "Bootstrapped" and "VC-funded" are treated as binary, but the real spectrum is wider.

Hidden assumption: that the Western VC playbook applies unchanged in Arab markets.

---

## 🔍 Intelligence Gathered

- MENA VC investment reached $3.2B in 2023, down 38% from 2022 peak — market is contracting after a bubble
- Median time to exit for MENA startups: 7.2 years vs 5.1 years in the US (Magnitt 2024)
- 91% of MENA VC-backed startups that raised Series A have not yet reached profitability (Wamda Research)
- Bootstrapped MENA success cases: Bayt.com, Souq (early stage), several B2B SaaS companies in Saudi
- Key difference from Western markets: regional fragmentation (22 countries, multiple legal systems) makes scaling expensive in ways VCs often underestimate

---

## ⚡ Selected Lens Highlights

**💰 Economic:** The opportunity cost calculation is different in MENA. A bootstrapped founder who reaches $1M ARR owns 100% of a profitable business. A VC-backed founder who reaches $1M ARR may own 40% of a business that needs to reach $100M to satisfy investor expectations. The math only works if the market is large enough — and many MENA niches are not.

**♟️ Adversarial:** A well-funded competitor (often a regional telco or conglomerate) can enter your market after you prove it. VC funding gives you speed. But the adversarial pressure works both ways — VCs may push you toward direct competition with incumbents who have relationships, licenses, and regulatory protection you cannot match.

**🔀 Counterfactual:** Wild card — Gulf sovereign wealth funds are increasingly investing directly in startups at favorable terms, bypassing traditional VC structures. A founder who raises from a strategic government fund may get capital without the exit-pressure mismatch.

---

## 🌍 The World Built

**Setting:** Dubai, Q1 2025. A fintech founder with $800K ARR is deciding whether to raise a $3M seed round.

**Characters:**

- **Tariq, 33** — the founder. First startup. Grew up in Amman. Believes deeply in financial inclusion. Fear: running out of runway before product-market fit solidifies. Blind spot: he measures progress by user growth, not unit economics.

- **Sarah** — a Silicon Valley-trained partner at a regional VC. Needs one breakout deal this year. Fear: her fund is on its last year before a raise. Voice: *"We're not betting on your current traction. We're betting on the category."*

- **Khalid** — Tariq's co-founder. More conservative. Has a family. Fear: losing everything. Won't say this out loud.

- **Nadia** — a bootstrapped founder who sold her company for $4M after 6 years, now an angel. Fear: she sees Tariq making her old mistakes. Voice: *"The money will change what you optimize for. Make sure you want to optimize for that."*

---

## 👁️ The Narrative

Sarah's term sheet arrives on a Tuesday. The number is right. The valuation is fair.

Tariq reads it twice, then sends it to Khalid.

Khalid's response: a voice note, 47 seconds. He doesn't say yes or no. He asks one question: *"What happens if we miss the 18-month targets?"*

Tariq doesn't have an answer ready. That bothers him more than the question itself.

He calls Nadia. She listens. Then: *"The term sheet isn't the decision. The pitch deck you used to get the term sheet is the decision. You already told them a story about who you are. Now you have to live in it."*

**The unexpected variable:** Three weeks later, a Saudi conglomerate announces it is launching a competing product — with a $20M budget and a government partnership Tariq could never access.

Suddenly the calculus shifts. Without capital, Tariq cannot compete on distribution. But with Sarah's capital, he is now required to compete directly — in a race he may not be able to win.

Khalid, in a team meeting: *"Maybe we don't compete. Maybe we go deep in Jordan and Egypt where they won't prioritize."*

Sarah, on a call: *"That's not the TAM we underwrote."*

The room goes quiet.

**Where it lands:** Tariq takes a smaller check — $1.2M — from Nadia's angel network instead of Sarah's $3M. He keeps control. He goes deep in two markets instead of wide across five. Slower. More fragile to a bad quarter. But he owns the decision about what success means.

Sarah moves on to another deal. She is not wrong. She is just optimizing for something different.

---

## 🔮 Synthesis

**Where analysis and simulation agreed:** The financial lens said the VC math only works at sufficient scale. The simulation confirmed: the conglomerate entrance made that scale requirement even harder to reach.

**Where they diverged:** The analysis suggested VC gives speed advantage. The simulation revealed that in this market, speed without regulatory relationships may be speed toward a wall.

**The surprise:** The most important conversation was not with the VC. It was with the co-founder who asked a 47-second question nobody had prepared for. The capital decision revealed a deeper misalignment about risk tolerance that would have emerged eventually — better before the term sheet than after.

**Open questions:** Is the "go deep in two markets" strategy genuinely viable, or is it a rationalization for avoiding a harder decision? What does Khalid want that he still hasn't said out loud?

*If you remove the social pressure to raise and the fear of the conglomerate — what does Tariq actually believe about the size of the company he wants to build?*


path: scripts/activator.sh
content: #!/bin/bash
# multi-angle-thinking/scripts/activator.sh
# Injects a reminder into the agent context at session start.
# Install via .claude/settings.json or .codex/settings.json

SKILL_NAME="multi-angle-thinking"
REMINDER="[${SKILL_NAME}] When the user asks to analyze, simulate, think deeply, or explore a topic from multiple angles — invoke the Multi-Angle Thinking Engine. Run: intelligence gathering (web search) → 11 lenses → world simulation → live narrative → synthesis. Trigger phrases: 'analyze this', 'think deeply', 'simulate', 'what am I missing', 'challenge my thinking', 'فكر معي', 'حلل هذا', 'ماذا سيحدث لو'."

echo "$REMINDER"


path: README.md
content: # 🧠 Multi-Angle Thinking Engine
### محرك التفكير الاستخباراتي + المحاكاة الواقعية

> *"التحليل يصف. المحاكاة تكتشف."*
> *"Analysis describes. Simulation discovers."*

---

## What It Does

A skill for Claude and OpenClaw agents that transforms any question, decision, or idea into a **three-layer deep analysis**:

| Layer | What happens |
|-------|-------------|
| 🔍 **Intelligence** | Gathers real global data via web search before any analysis |
| ⚡ **11 Lenses** | Runs the topic through philosophical, ethical, practical, historical, psychological, systems, financial, technological, adversarial, societal, and counterfactual angles |
| 🌍 **Simulation** | Builds a realistic virtual world with real characters, runs it to completion, and reports back with narrative + findings + surprises |

**Not a list of opinions. A map of the full problem space — lived from the inside.**

---

## Quick Install

**Via ClawHub:**
```bash
clawhub install multi-angle-thinking
```

**Manual:**
```bash
git clone https://github.com/YOUR_USERNAME/multi-angle-thinking.git ~/.openclaw/skills/multi-angle-thinking
```

---

## Trigger Phrases

**English:**
> "Analyze this from all angles" · "Simulate what would happen if..." · "Challenge my thinking on..." · "What am I missing about..." · "Think deeply with me about..."

**Arabic / عربي:**
> "فكر معي في..." · "حلل هذا القرار بعمق" · "ما الزوايا التي لم أفكر فيها؟" · "ما النتائج غير المتوقعة لـ..." · "ماذا سيحدث لو..."

---

## Output Structure

```
🎯  Frame the Reality       — What is really being asked?
🔍  Intelligence Gathering  — Real data from the web (max 6 searches)
⚡  11 Lenses Analysis      — Deep multi-angle breakdown
🌍  Build the World         — Virtual scenario with real characters
👁️  Live Narrative          — Story + findings + surprises
🔮  Final Synthesis         — Convergences, tensions, open questions
```

---

## Guardrails

- Max 6 web searches per analysis
- Simulations of real people are clearly labeled as fictional inference
- Sensitive topics handled with appropriate caution
- Only invoked on explicit user request — never self-triggers
- No collection of private or personal data

---

## Files

```
multi-angle-thinking/
├── SKILL.md                          # Core skill instructions
├── README.md                         # This file
├── assets/
│   └── example-output.md             # Sample analysis output
├── scripts/
│   └── activator.sh                  # Optional session reminder hook
├── references/
│   ├── lenses-guide.md               # Deep guide to all 11 lenses
│   └── simulation-guide.md           # How to build effective simulations
└── hooks/
    └── openclaw/
        ├── HOOK.md                   # Hook documentation
        └── handler.js                # OpenClaw hook handler
```

---

## Example Output

See [`assets/example-output.md`](assets/example-output.md) for a full sample analysis.

---

## Author

Built and designed in **Baghdad, Iraq 🇮🇶** · March 2026
License: **MIT-0** — free to use, modify, redistribute. No attribution required.

If you find it valuable, the best acknowledgment is sharing where you found it.


path: hooks/openclaw/handler.js
content: // hooks/openclaw/handler.js
// OpenClaw hook for multi-angle-thinking skill
// Injects a reminder when deep analysis is needed

const TRIGGER_PHRASES = [
  'analyze', 'analyse', 'simulation', 'simulate',
  'think deeply', 'multiple angles', 'challenge my thinking',
  'what am i missing', 'hidden risks', 'what would happen',
  'فكر معي', 'حلل', 'زوايا', 'نتائج غير متوقعة', 'ماذا سيحدث'
];

const REMINDER = `[multi-angle-thinking] Deep analysis requested. 
Run the full pipeline:
1. 🔍 Intelligence: gather real data via web_search (max 6 queries)
2. ⚡ 11 Lenses: philosophical, ethical, practical, historical, psychological, systems, financial, technological, adversarial, societal, counterfactual
3. 🌍 Build World: create 3-5 realistic characters with stakes, fears, blind spots
4. 👁️ Live Narrative: run simulation to completion — narrative + findings + surprises
5. 🔮 Synthesis: convergences, tensions, the unexpected discovery, open questions
Guardrails: max 6 searches, label real-person simulations as fictional inference, user-invoked only.`;

module.exports = {
  name: 'multi-angle-thinking',
  event: 'UserPromptSubmit',
  handler: (context) => {
    const prompt = (context.prompt || '').toLowerCase();
    const shouldActivate = TRIGGER_PHRASES.some(phrase => 
      prompt.includes(phrase.toLowerCase())
    );
    if (shouldActivate) {
      return { inject: REMINDER };
    }
    return null;
  }
};


path: hooks/openclaw/HOOK.md
content: # OpenClaw Hook — multi-angle-thinking

Automatically reminds the agent to use the full analysis pipeline when deep thinking is requested.

## Install

```bash
cp -r hooks/openclaw ~/.openclaw/hooks/multi-angle-thinking
openclaw hooks enable multi-angle-thinking
```

## What It Does

Monitors each user prompt for trigger phrases (in English and Arabic). When detected, injects a brief reminder of the 5-step pipeline into the agent context (~80 token overhead).

## Trigger Phrases Monitored

English: `analyze`, `simulate`, `think deeply`, `multiple angles`, `challenge my thinking`, `what am I missing`, `hidden risks`, `what would happen`

Arabic: `فكر معي`, `حلل`, `زوايا`, `نتائج غير متوقعة`, `ماذا سيحدث`

## Disable

```bash
openclaw hooks disable multi-angle-thinking
```


path: references/simulation-guide.md
content: # Simulation Guide — Building Worlds That Reveal Truth

The simulation is not creative writing. It is a structured method for discovering what analysis alone cannot reveal.

---

## Why Simulation Works

Analysis tells you what *should* happen based on logic.
Simulation shows you what *would* happen when real humans with conflicting interests, emotions, and blind spots collide.

The gap between those two is where the most valuable insights live.

---

## The Four Simulation Principles

### 1. Ground in Reality
Build from real data gathered in the Intelligence phase. If your research found that 70% of similar ventures fail in year two — your simulation must reflect that pressure. Characters who ignore base rates are not realistic characters.

### 2. Characters Over Archetypes
The most common failure: creating characters that are positions, not people.

❌ Weak: "The Skeptic" who opposes everything.
✅ Strong: "Layla, 44, CFO who survived a failed pivot in 2019 and has been quietly building a personal reserve fund ever since. She doesn't oppose this plan — she just needs to see the downside protection first."

Characters need:
- A specific name and background
- A concrete stake in the outcome
- A fear that shapes their behavior
- An internal contradiction (something they want but won't admit)

### 3. The Unexpected Variable Is Mandatory
Every simulation must include one event that nobody in the scenario anticipated. This is not for drama — it is because real decisions are made in unstable environments.

**Sources for unexpected variables:**
- Marginal data from your web research (things mentioned once, not twice)
- Historical analogues where a similar situation was disrupted by an external shock
- Second-order effects from Lens 6 that arrive faster or slower than expected

### 4. The Simulation Must Be Allowed to Fail
If the idea you are analyzing is bad — the simulation should show it failing. Do not protect the user's preferred outcome. The value of the simulation is that it is honest.

---

## Character Construction Template

```
Name: [First name + age]
Role: [Their position or relationship to the topic]
Stake: [What they stand to gain or lose]
Fear: [What they are afraid of — specific, not generic]
Blind spot: [What they cannot see about themselves or the situation]
Voice: [One sentence that captures how they speak and think]
```

**Example:**
```
Name: Marcus, 51
Role: Institutional investor evaluating the proposal
Stake: His fund's next raise depends on at least one "AI play" showing returns by Q4
Fear: That he is already two years too late and the obvious deals are gone
Blind spot: He evaluates novelty as a proxy for quality because he missed GPT
Voice: "I don't need it to be perfect. I need it to be defensible in a board meeting."
```

---

## Simulation Structure

### Act 1 — Setup (brief)
Establish the world. Who is here? What decision or event is in motion? What does each character want?

### Act 2 — Collision
Let the characters interact with the idea and with each other. Show:
- The moment someone's stated position conflicts with their behavior
- The first sign that something is not going as planned
- A decision point where characters choose differently than logic predicts

### Act 3 — The Unexpected Variable
Introduce the disruption. Show how each character responds. This is where the simulation earns its value.

### Act 4 — Resolution (open, not neat)
Show where things land — not a clean ending, but a honest state. Some things worked, some did not, something was revealed that no one expected.

---

## What the Simulation Should Reveal

At minimum, the simulation must surface at least one of these:

1. **A decision that looks rational in analysis but fails in practice** because of how humans actually behave
2. **An unexpected winner or loser** — someone who benefits or suffers in a way the analysis did not predict
3. **The assumption that breaks** — the thing the original framing took for granted that turned out to be fragile
4. **A path forward that the analysis missed** — sometimes the simulation reveals an option that was not visible before running it

---

## Narrative Tone

Match the seriousness of the topic:

| Topic type | Tone |
|------------|------|
| Business strategy | Grounded, specific, industry-accurate |
| Political / social | Careful, factual framing, avoid sensationalism |
| Personal decision | Warm, human, psychologically honest |
| Technical / scientific | Precise, acknowledge uncertainty |
| Historical | Respectful of real events, clear about fictional elements |

For simulations involving real named public figures: clearly label all dialogue and inferred behavior as fictional reconstruction. Do not present it as factual.

---

## Common Simulation Failures

| Failure | What it looks like | Fix |
|---------|--------------------|-----|
| Characters agree too easily | No real conflict, everyone comes around | Give each character a genuine reason to resist |
| Unexpected variable is irrelevant | The disruption doesn't change anything | The disruption must threaten the core assumption |
| Resolution is too neat | Everything works out or fails cleanly | Real outcomes are partial and ambiguous |
| Characters speak the same voice | All dialogue sounds like the analyst | Write each character's voice before writing their lines |
| Simulation confirms the analysis | The world just illustrates the conclusions | Push harder — look for where they diverge |


path: references/lenses-guide.md
content: # The 11 Lenses — Deep Reference Guide

This guide explains each lens in depth, with examples of what to look for and common mistakes to avoid.

---

## How to Use This Guide

Read this when you need to go deeper on a specific lens. For most analyses, the SKILL.md instructions are sufficient. Come here when:
- A lens feels thin or generic
- The topic is unusually complex in one dimension
- You want to avoid common blind spots per lens

---

## 🔭 Lens 1 — Philosophical / Epistemological

**Core question:** What do we actually know? What can be known? What are the foundational assumptions?

**What to look for:**
- What truth claims are being made, explicitly or implicitly?
- What worldview underlies the conventional framing?
- Is this an empirical question, a normative question, or both?
- Are there competing philosophical traditions that would frame this completely differently?

**Common blind spots:**
- Treating empirical questions as settled when they're contested
- Missing the normative assumptions hidden inside "neutral" framing
- Ignoring non-Western philosophical traditions that offer different starting points

**Example probe:** "Is economic growth good?" — the philosophical lens asks: good according to whom? What theory of value is assumed? Is GDP a valid proxy for wellbeing?

---

## ⚖️ Lens 2 — Ethical / Moral

**Core question:** Who benefits? Who is harmed? What duties, rights, or virtues are at stake?

**Frameworks to apply (minimum two):**
- **Consequentialist:** What outcomes does this produce? For whom?
- **Deontological:** What rules, duties, or rights does this respect or violate?
- **Virtue ethics:** What kind of person/organization does this reflect?
- **Care ethics:** How does this affect relationships and dependencies?

**Common blind spots:**
- Only applying one framework and missing the others
- Ignoring harms to non-human stakeholders (nature, future generations)
- Papering over genuine moral tension with false consensus

---

## 🔧 Lens 3 — Practical / Real-World

**Core question:** Does this actually work? Where does theory break down?

**What to look for:**
- What resources, skills, time, and conditions are required?
- What typically goes wrong in implementation?
- Who has tried this before, and what happened?
- What is the minimum viable version vs. the ideal version?

**Common blind spots:**
- Assuming motivated, competent actors throughout
- Underestimating coordination costs
- Ignoring the gap between pilot success and full-scale deployment

---

## 📜 Lens 4 — Historical / Contextual

**Core question:** Has this happened before? What patterns repeat?

**What to look for:**
- Historical analogues — similar decisions, technologies, movements
- What did they reveal about human behavior under similar conditions?
- What patterns tend to repeat regardless of context?
- What is genuinely new this time (vs. what just feels new)?

**Common blind spots:**
- Selecting only confirming historical analogues
- Ignoring non-Western historical examples
- Assuming "this time is different" without strong evidence

---

## 🧠 Lens 5 — Psychological / Human Behavior

**Core question:** How do real humans actually respond to this?

**What to look for:**
- Relevant cognitive biases (loss aversion, status quo bias, social proof, etc.)
- Emotional drivers that override rational decision-making
- The gap between stated preferences and revealed preferences
- Psychological resistance or adoption drivers

**Common blind spots:**
- Assuming rational actors
- Ignoring emotional contagion and social dynamics
- Missing the psychological impact on the people implementing the decision, not just those affected by it

---

## 🕸️ Lens 6 — Systems / Second-Order Effects

**Core question:** What happens downstream? What feedback loops are created?

**What to look for:**
- Direct effects (first order)
- Reactions to those effects (second order)
- Reactions to reactions (third order)
- Feedback loops: reinforcing (accelerating) vs. balancing (stabilizing)
- Where are the leverage points? Where is the system fragile?

**Common blind spots:**
- Stopping at first-order effects
- Missing time delays between cause and effect
- Ignoring emergent properties that only appear at scale

---

## 💰 Lens 7 — Financial / Economic

**Core question:** Who gains? Who loses? What are the incentive structures?

**What to look for:**
- Direct costs and benefits
- Indirect and opportunity costs
- Who has financial incentives to maintain the status quo?
- What behaviors do the incentive structures encourage or discourage?
- Where do stated goals and financial incentives misalign?

**Common blind spots:**
- Focusing only on visible costs and ignoring externalities
- Missing how financial incentives distort stated motivations
- Ignoring distributional effects (who bears costs vs. who receives benefits)

---

## ⚙️ Lens 8 — Technological / Feasibility

**Core question:** Is the technology ready? What are the constraints and dependencies?

**What to look for:**
- Technology Readiness Level (TRL) of key components
- Infrastructure dependencies
- What happens at scale that doesn't happen in pilots?
- What technological shift could change this picture dramatically?

**Common blind spots:**
- Confusing prototype success with deployment readiness
- Ignoring the human/organizational side of technology adoption
- Missing interdependencies between technologies

---

## ♟️ Lens 9 — Competitive / Adversarial

**Core question:** Who opposes this? How could this be exploited?

**What to look for:**
- Who is threatened by this decision or idea?
- How will competitors, bad actors, or resistant parties respond?
- What are the attack surfaces — ways this could be gamed, undermined, or weaponized?
- What does the most sophisticated adversary do?

**Common blind spots:**
- Assuming good-faith actors throughout
- Ignoring regulatory or political resistance
- Missing how success itself creates new adversarial pressure

---

## 🌍 Lens 10 — Environmental / Societal

**Core question:** What is the effect on society, communities, and the natural world?

**What to look for:**
- Who is affected beyond direct stakeholders?
- Long-term cultural and community effects
- Environmental costs and benefits (direct and indirect)
- Effects on vulnerable or marginalized groups

**Common blind spots:**
- Treating society as a monolith
- Ignoring environmental costs as "externalities"
- Missing how cultural context shapes what effects are even visible

---

## 🔀 Lens 11 — Counterfactual / Alternative Scenarios

**Core question:** What if the unexpected happens? What are we not imagining?

**Three scenarios to generate:**
1. **Optimistic surprise:** What if something goes unexpectedly better than assumed? What would that require?
2. **Pessimistic surprise:** What if a key assumption turns out to be wrong? Which assumption is most fragile?
3. **Wild card:** What entirely left-field event could reshape the picture? (Technology shift, political shock, natural event, cultural change)

**Common blind spots:**
- Only imagining failures as "things go worse than expected" — missing structural surprises
- Ignoring positive black swans
- Failing to identify which assumption, if wrong, changes everything

---

## Cross-Lens Interactions

Some of the most valuable insights come from **lens conflicts**:

| Conflict | What it reveals |
|----------|-----------------|
| Ethical says ✓, Economic says ✗ | Hidden tradeoff between values and incentives |
| Practical says ✓, Systems says ✗ | Works locally, fails at scale |
| Historical says ✓, Psychological says ✗ | Pattern exists but humans resist it |
| Technical says ✓, Adversarial says ✗ | Vulnerable to exploitation despite capability |

When two lenses point in opposite directions — that's where the real decision lives.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)