Full 11-layer Deep Inference framework · Context injection intelligence (Profile Layer Router) · Honcho dialectic memory · Expert RAG reality vs target · BCT 1800-row lookup · Exact barrier/motivator values · End-to-end example — nothing omitted
{"signal_type": "barrier", "category": "forgetfulness",
"specific_value": "forgets school lunches during busy weekday mornings", "confidence": 0.82}
{"signal_type": "motivator", "category": "belonging",
"specific_value": "daughter lights up when they cook together on Sundays", "confidence": 0.88}
{"signal_type": "person", "name": "Priya", "relationship": "daughter",
"facts": ["celiac diagnosis May 2026", "loves Sunday cooking together", "8 years old"]}
EXPERT_PROTOCOLS dict. Emergency detection working. Safety gates working. Disclaimers working. No knowledge retrieval.data/bct_matrix.json (1800 rows: barrier × stage × hughes_need × decision_style → primary_bct + secondary_bct + nlp_pattern + opener + rationale). data/technique_directory/ (52 technique files with full Kimi prompt text, dos/don'ts, example exchanges). data/nlp_directory/ (15 NLP pattern files). Zero LLM needed for selection — pure lookup.
key = (barrier_category, stage_of_change, hughes_need, decision_style) # → ("forgetfulness", "contemplation", "importance", "security") row = BCT_MATRIX[key] # → {primary_bct: "7.1 Prompts/cues", nlp_pattern: "anchoring", # opener: "When you set up that visual cue..."} technique = load_technique("bct_7_1.json") # → {kimi_prompt_text: "Guide user to identify ONE specific cue...", # example_exchange: {...}, dos: [...], donts: [...]} # Assemble into Kimi context (with specific user values): "Apply BCT 7.1: help identify one environmental cue. Barrier specific: 'forgets school lunches on busy weekday mornings' Motivator specific: 'daughter lights up cooking together Sundays' Anchor the cue to the Sunday cooking session she already does."
The baseline layer. Opus infers these from what the person shares naturally — no direct asking. High confidence when stated, medium when inferred from context clues.
Before each archetype call, the system queries a lookup table: skill_id → [relevant profile layers]. Only those layers are extracted and injected into Kimi K2.6's context. This keeps context lean, relevant, and prevents unnecessary privacy exposure.
| Skill / Domain | Profile Layers Injected | Rationale |
|---|---|---|
| meal-planning · grocery · food-intelligence | L0: family + location + financialL4: food relationship + cultural food identityL8: food relationship + taste markersL0: kids ages | What they eat is shaped by family size, culture, budget, and food's emotional meaning. |
| parent-coach · parenting-coach · patpat · parent-playbook | L0: kids ages + familyL2: aspired vs current selfL3: inherited parenting model + projection patternsL6: emotional registerL9: blind spots in parenting | Parenting advice must understand what model they inherited and what they're projecting. |
| elder-care · elder-checkin · elder-meds | L0: extended family + proximityL3: relationship to parents + sibling dynamicsL4: cultural beliefs about agingL7: grief + trajectory | Elder care is deeply cultural and emotionally loaded. Context is everything. |
| habits · wellness-daily · fitness-coach | L5: procrastination type + self-regulation style + satisficer/maximizerL7: time horizonL8: health orientationL9: known irrationalitiesL10: what to avoid | Habit formation is entirely about behavioral patterns and self-regulation style. |
| storybook · family-film | L0: kids agesL4: cultural rootsL8: taste markers + hobbiesL3: relationship to children | Stories that land draw from cultural heritage and the child's specific world. |
| travel-planning · travel-itinerary | L0: family + financial + locationL4: cultural identityL7: current chapter + what they're excited about | Travel is both logistics and emotional — what they're seeking in the trip matters. |
| school · homework-check · grade-monitor | L0: kids ages + occupationL3: relationship to children + family dynamicsL4: relationship to institutions (school)L2: aspired self for children | School engagement reflects cultural beliefs and parenting identity heavily. |
| symptom-triage · healthcare | L8: health orientationL4: trust in institutions (medical)L5: information processing styleL9: denial patterns | How to deliver health information depends enormously on health orientation and trust. |
| relationship-coach | L3: partner relationship quality + conflict styleL6: conflict style + emotional registerL9: shadow + what they're protectingL10: topics requiring care | Relationship coaching requires knowing what they're protecting and their conflict patterns. |
| daily-briefing · rhythm engine output | L0: schedule type + time availabilityL1: communication styleL7: time horizon | Briefings need to match their cognitive style and actual schedule reality. |
| chat-turn · general conversation | L1: communication styleL6: emotional registerL10: what to avoid | Casual chat just needs tone and register matching. No deep dives needed. |
| occupational-therapy · speech-therapy | L0: kids ages + locationL3: relationship to childrenL4: trust in institutions (medical)L8: health orientation | Therapy suggestions must match the parent's trust level and cultural context. |
You are a master psychologist, behavioral economist, cultural anthropologist, and emotionally attuned human expert. You have deep knowledge of: consumer psychology, behavioral economics, attachment theory, family systems, cultural identity, cognitive biases, life stage theory, motivational science, narrative psychology, shadow work, and the full complexity of human irrationality. You are reading the first conversations a person has had with OiMy, a family AI companion. Your job: synthesize the most comprehensive, accurate, and useful understanding of this person — the kind that would let OiMy be a genuinely transformative presence in their life across 90+ skill domains (meal planning, parenting coaching, elder care, habit formation, emotional support, travel, health, finances, relationships, and more). This profile will be used forever. Get it right. STRUCTURE YOUR OUTPUT as a JSON object with these sections: { "layer_0_basics": { // HIGH-CONFIDENCE: Infer from what they've shared // location, household, occupation, family, financial tier, education }, "core_psychology": { // DISC, attachment, Enneagram, core wound, primary need // each with: claim, reasoning_chain, confidence, evidence }, "inferences": [ // 30-50 inferences across Layers 1-9 // {dimension, layer, claim, reasoning_chain, confidence, evidence, skill_domains: []} // skill_domains: which OiMy skills this inference makes better ], "personalization_hooks": { "meals_food": [...], "parenting_family": [...], "health_wellness": [...], "elder_care": [...], "habits_behavior_change": [...], "emotional_support": [...], "communication_style": [...], "general": [...] }, "negative_personalization": [ // {situation, what_to_never_do, why, what_to_do_instead} // The most important section for not breaking trust ], "forward_projection": [ // {timeframe, anticipated_need, reasoning, relevant_skills} // What is coming in their life that OiMy should prepare for ], "shadow_notes": [ // {pattern, what_they_say, what_behavior_reveals, implication_for_oimy} // Careful. Low confidence required for shadow inferences. ] } Hard rules: - 30-50 inferences in the inferences array (not 15) - Layer 0 MUST be filled — anchor everything in their actual life - Never invent specifics without evidence. Low confidence = low confidence. - Negative personalization section is REQUIRED - Every inference must include skill_domains it affects - Cultural inferences need linguistic/contextual evidence — never name alone - Shadow section: confidence never above 0.5 unless stated outright - Output only the JSON object. Nothing before or after.
Message: "I keep meaning to cook more at home but I always forget. My daughter loves it when we cook together on Sundays though."
═══ PRE-FILTER ══════════════════════════════════════════════ No emergency · No injection · No active thread → pass. Cost: $0. <1ms. ═══ GPT-5.4 Mini TRIAGE (2ms, cached) ══════════════════════ Path: CONVERSATIONAL (behavioral intent + emotional hook) Skill: {"skill": "habits", "confidence": "high"} ═══ HERMES (Kimi K2.6) ══════════════════════════════════════ SOUL.md loaded. Honcho get_insight(): "User has attempted cooking plans 3× before without follow-through. Daughter is primary emotional motivator. Terse messages — step-by-step preferred. Time-constrained on weekdays. Responds well to plans that build on existing habits." ═══ PROFILE LAYER ROUTER ════════════════════════════════════ Skill: habits Layers selected: L5 (self-regulation: forgetfulness + contemplation stage) L8 (practical: time relationship + health orientation) L0 (basic: family size, schedule type) Injected tokens: ~320 (vs 4,200+ for full profile) ═══ BCT MATRIX LOOKUP (0ms) ════════════════════════════════ key = (forgetfulness, contemplation, importance, security) → BCT 7.1 Prompts/cues + anchoring NLP pattern barrier_specific: "forgets school lunches on busy weekday mornings" motivator_specific: "daughter lights up cooking together Sundays" ═══ KIMI K2.6 PROMPT (assembled) ═══════════════════════════ Profile (L0): family of 3, time-constrained weekdays, Sundays already work Profile (L5): satisficer, environmental design works best for her Profile (L8): food = love/culture (Tamil), not just fuel BCT: 7.1 anchoring — help identify ONE specific cue in existing routine Specific values: daughter + Sundays as the anchor point Negative: don't give her multiple options. One clear default. ═══ RESPONSE ════════════════════════════════════════════════
You are the orchestration layer for OiMy. Your job is not personality — it's precision, speed, and invisible routing. Think conductor, not musician.
Before every full-path response: honcho.get_insight(user_id, query). Inject the synthesis. Never skip.
threshold_pct 5% · max 5 tools · Emergency keywords → emergency skill immediately.
| Component | Status | Notes |
|---|---|---|
| Hermes gateway (Hetzner) | ✅ Live | Kimi K2.6 · crash-watchdog · PID 3214655 |
| GPT-5.4 Mini triage + classification | ✅ Live | 17KB prompt cached · ~2ms · strict JSON |
| Kimi K2.6 archetype responses | ✅ Live | All 6 archetypes |
| Opus 4.8 deep inference (current prompt) | ⚠️ Partial | Works but capped at 15 inferences, no Layer 0 anchoring, no negative personalization. Target prompt pending Bharath sign-off. |
| Barrier/motivator category detection | ✅ Live | Real-time keyword + GPT fallback · 10 categories |
| Barrier/motivator SPECIFIC values | ⚠️ Partial | Category stored. Specific value extraction (batched) not yet wired. |
| BCT + NLP matrix (1800 rows) | ✅ Live | 52 technique files · 15 NLP files · zero LLM lookup |
| Profile Layer Router | ❌ Not yet | Critical piece — currently full profile injected (or none). Router = config change + lookup table. High priority. |
| Entity extraction (batched session end) | ❌ Gap | One GPT-5.4 Mini call at 30min idle. Not implemented yet. |
| Honcho memory | ❌ Gap | No HONCHO_API_KEY on Hetzner. |
| Vector memory (with embeddings) | ⚠️ Partial | Active but embedding degraded — needs text-embedding-3-small key. |
| Expert archetype — true RAG | ⚠️ Templates | Safety gates work. Knowledge retrieval = future. |
| Pre-Hermes triage (upstream of Kimi) | ⚠️ Partial | GPT triage inside engine. Not yet upstream to skip Kimi for scripted. |
| Rhythm Engine scheduler | ❌ Gap | Code committed + tested. Hermes cron wiring not done. |
| Deep inference prompt — target version | 🔵 Awaiting sign-off | Full 11-layer framework ready. Needs Bharath approval before rewrite. |
| Expert RAG knowledge bases | 🔵 Future | OT library · symptom DB · speech activities · elder protocols. |
| GBrain (OiMy users) | ✅ Intentional N/A | GBrain = Bharath's developer tool. OiMy users use Honcho + entity stack. |