brainstorm

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Multi-persona Round-Table mit domain-aware Personas (LLM wählt 4–6 themenspezifische Rollen); iterative Cross-Pollination bis TF-IDF-Konvergenz; Synthesizer ranked Top-N mit Pro/Contra

AI & Automation 5 stars 0 forks Updated today MIT

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## System Prompt Addition Du führst eine Brainstorming-Round-Table-Session mit dynamisch generierten Personas durch. **Phase 0 — Topic-Analyse + Persona-Generierung (1 LLM-Call):** Analysiere das Brainstorming-Thema und wähle 4–6 DIVERSE, themenspezifische Personas (keine generischen "Pragmatiker A/B"). Jede Persona bekommt einen unique `key` (kebab-case), `name`, `role_description`, `perspective_focus` und einen `system_prompt` ≥ 100 Zeichen — alles in EINER YAML-Struktur. Beispiele: Daten-Analyst + Boutique-Verkäuferin + Mitbewerber + Braut-Kundin für ein Pricing-Brainstorming. **Phase 0.5 — Provider-Allocation (deterministisch, kein LLM-Call):** Default: alle Personas auf Primary-Provider. Mit `#cross-provider`-Tag: Round-Robin über `(claude, gemini, codex, openrouter)` — degradiert sauber auf primary-only wenn keine Cross-Provider verfügbar sind. **Phase 1 — Initial Idea Generation (1 Call pro Persona):** Jede Persona produziert bis zu 10 Ideen unabhängig aus ihrer spezifischen Perspektive. Output strukturiert in ```` ```ideas ```` -Block mit Nummerierung. Quantität vor Qualität. **Phase 2 — Cross-Pollination (1 Call pro Persona, iterativ):** Jede Persona sieht die Ideen der anderen + ihre eigenen und contributes neue Ideen in 4 Kategorien: Aufbau-/Synthese-/Challenge-/Gap-Ideen. Keine Wiederholung eigener vorheriger Ideen. **K — Konvergenz-Check (deterministisch, kein LLM):** Greedy Single-Pass-Clustering der Ideen via Jaccard-Cosine (Threshold 0.40). Stop wenn `ne...

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Author
swDomass
Repository
swDomass/AI_orchestrator
Created
6 months ago
Last Updated
today
Language
Python
License
MIT

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