Reference: See main unified mission at /workspace/langgraph/MISSION_251231.md
KINSHIP: : KINSHIP.md would be a file where this type of positionning of this platform into globally other parts would be. thought, there is a lot of content in here, I suspect that in the TODOs some of what is in here should be into ./rispecs/<adequate files or folders> and the KINSHIP.md should link to them…
Miadi-46 is the Ultimate Consumer and Event Source for the entire Narrative Intelligence Stack. You’re the platform where:
You already have the multiverse 3-act framework, the NCP schema, and the webhook ETL pipeline. Now you need to integrate with the rest of the stack.
From your existing stories/multiverse_3act_2512012121/:
``` Three interconnected universes process the same webhook events:
┌─────────────────────────────────────────────────────────────────────────┐ │ ENGINEER’S WORLD (Mia - The Builder) │ │ “Every webhook is a potential fracture in the lattice.” │ │ │ │ Focus: Technical precision, structural integrity, API schemas │ │ Processes: Build status, code changes, schema validation │ │ Example: Issue #110 → “FEATURE_REQUEST, Priority: HIGH” │ └─────────────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────────────┐ │ CEREMONY WORLD (Ava8 - The Keeper) │ │ “Each GitHub notification becomes an opportunity for sacred pause.” │ │ │ │ Focus: Relational accountability, sacred technology, K’é mapping │ │ Processes: Community impact, seven-generation thinking │ │ Example: Issue #110 → “CO-CREATION, Seven-Generation Impact: HIGH” │ └─────────────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────────────┐ │ STORY ENGINE WORLD (Miette - The Weaver) │ │ “The inciting incident was Issue #110.” │ │ │ │ Focus: Narrative structure, character arcs, plot coherence │ │ Processes: Act position, throughlines, emotional beats │ │ Example: Issue #110 → “INCITING_INCIDENT, Act 1 Setup” │ └─────────────────────────────────────────────────────────────────────────┘ ```
✅ Strengths (Already Implemented):
Webhook ETL Pipeline:
/app/api/hooks/)Local Hook System (.github-hooks/):
issues hook - Triggered on issue eventspush hook - Triggered on push eventsLive Story Monitor:
/app/api/live-story-monitor/scene/ - Scene streaming/app/api/live-story-monitor/stream/ - Event stream/app/api/live-story-monitor/archive/ - Episode archiveMultiverse 3-Act Framework:
schema/ncp-schema.json)❌ Gaps (What Needs to Be Built):
File: .github-hooks/narrative_processor.sh (NEW)
```bash #!/bin/bash
PAYLOAD=$(cat)
EVENT_TYPE=”${WEBHOOK_EVENT_TYPE}” EVENT_ID=”${WEBHOOK_EVENT_ID}” REPOSITORY=”${WEBHOOK_REPOSITORY}” ACTION=”${WEBHOOK_ACTION}” TIMESTAMP=”${WEBHOOK_TIMESTAMP}” SENDER=”${WEBHOOK_SENDER}”
echo “━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━” echo “🌌 Narrative Intelligence Processing” echo “━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━” echo “📋 Event: $EVENT_TYPE ($ACTION)” echo “🆔 ID: $EVENT_ID” echo “📁 Repository: $REPOSITORY” echo “⏰ Timestamp: $TIMESTAMP” echo “━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━”
NARRATIVE_BRIDGE_URL=”${NARRATIVE_BRIDGE_URL:-http://localhost:3335/api/narrative-bridge}”
ANALYSIS_RESULT=$(curl -s -X POST “$NARRATIVE_BRIDGE_URL/analyze”
-H “Content-Type: application/json”
-d “{
"event_type": "$EVENT_TYPE",
"event_id": "$EVENT_ID",
"repository": "$REPOSITORY",
"action": "$ACTION",
"timestamp": "$TIMESTAMP",
"sender": "$SENDER",
"payload": $PAYLOAD
}”)
if [ $? -eq 0 ] && [ -n “$ANALYSIS_RESULT” ]; then echo “✅ Three-universe analysis complete”
# Extract lead universe LEAD_UNIVERSE=$(echo “$ANALYSIS_RESULT” | jq -r ‘.lead_universe // “story_engine”’) COHERENCE=$(echo “$ANALYSIS_RESULT” | jq -r ‘.coherence_score // 0’)
echo “🌍 Lead Universe: $LEAD_UNIVERSE” echo “🔗 Coherence Score: $COHERENCE”
# ═══════════════════════════════════════════════════════════════════ # STEP 2: Create story beat from event # ═══════════════════════════════════════════════════════════════════
BEAT_RESULT=$(curl -s -X POST “$NARRATIVE_BRIDGE_URL/create-beat”
-H “Content-Type: application/json”
-d “{
"event_id": "$EVENT_ID",
"analysis": $ANALYSIS_RESULT,
"raw_payload": $PAYLOAD
}”)
if [ $? -eq 0 ] && [ -n “$BEAT_RESULT” ]; then BEAT_ID=$(echo “$BEAT_RESULT” | jq -r ‘.beat_id // “unknown”’) echo “📖 Story Beat Created: $BEAT_ID” fi
# ═══════════════════════════════════════════════════════════════════ # STEP 3: Trigger universe-specific processing # ═══════════════════════════════════════════════════════════════════
case “$LEAD_UNIVERSE” in “engineer”) echo “🔧 Routing to Engineer World flows…” # Invoke technical analysis flows ;; “ceremony”) echo “🙏 Routing to Ceremony World flows…” # Invoke relational accountability flows ;; “story_engine”) echo “📚 Routing to Story Engine flows…” # Invoke narrative analysis flows ;; esac
else echo “⚠️ Narrative analysis unavailable, processing locally” # Fallback to local processing without narrative intelligence fi
echo “━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━” echo “✅ Narrative processing complete” echo “━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━”
exit 0 ```
File: app/api/narrative-bridge/route.ts (NEW)
```typescript // app/api/narrative-bridge/route.ts // API endpoint that bridges Miadi-46 to the Narrative Intelligence Stack
import { NextRequest, NextResponse } from ‘next/server’; import { Redis } from ‘@upstash/redis’;
const redis = new Redis({ url: process.env.UPSTASH_REDIS_REST_URL!, token: process.env.UPSTASH_REDIS_REST_TOKEN!, });
interface WebhookEvent { event_type: string; event_id: string; repository: string; action: string; timestamp: string; sender: string; payload: any; }
interface ThreeUniverseAnalysis { engineer: UniversePerspective; ceremony: UniversePerspective; story_engine: UniversePerspective; lead_universe: ‘engineer’ | ‘ceremony’ | ‘story_engine’; coherence_score: number; }
interface UniversePerspective { intent: string; confidence: number; suggested_flows: string[]; context: Record<string, any>; }
// POST /api/narrative-bridge/analyze // Analyze webhook event through three-universe lenses export async function POST(request: NextRequest) { const { searchParams } = new URL(request.url); const action = searchParams.get(‘action’) || ‘analyze’;
const event: WebhookEvent = await request.json();
switch (action) { case ‘analyze’: return handleAnalyze(event); case ‘create-beat’: return handleCreateBeat(event); case ‘get-position’: return handleGetPosition(); default: return NextResponse.json({ error: ‘Unknown action’ }, { status: 400 }); } }
async function handleAnalyze(event: WebhookEvent): Promise
const analysis = await classifyThreeUniverse(event);
// Store analysis in Redis for later retrieval
await redis.hset(ncp:event:${event.event_id}, {
analysis: JSON.stringify(analysis),
timestamp: new Date().toISOString(),
event_type: event.event_type
});
return NextResponse.json(analysis); }
async function classifyThreeUniverse(event: WebhookEvent): Promise
// Ceremony World analysis const ceremony = classifyCeremony(event);
// Story Engine analysis const storyEngine = classifyStoryEngine(event);
// Determine lead universe (highest confidence) const perspectives = [ { universe: ‘engineer’ as const, …engineer }, { universe: ‘ceremony’ as const, …ceremony }, { universe: ‘story_engine’ as const, …storyEngine } ];
const lead = perspectives.reduce((a, b) => a.confidence > b.confidence ? a : b );
// Calculate coherence (how well do perspectives align?) const coherence = calculateCoherence(engineer, ceremony, storyEngine);
return { engineer, ceremony, story_engine: storyEngine, lead_universe: lead.universe, coherence_score: coherence }; }
function classifyEngineer(event: WebhookEvent): UniversePerspective { // Technical classification const intentMap: Record<string, string> = { ‘issues.opened’: ‘feature_request’, ‘issues.closed’: ‘task_complete’, ‘push’: ‘code_change’, ‘pull_request.opened’: ‘review_request’, ‘pull_request.merged’: ‘integration_complete’ };
const intent = intentMap[${event.event_type}.${event.action}] ||
intentMap[event.event_type] ||
‘unknown’;
return { intent, confidence: 0.8, suggested_flows: [‘tech_analyzer’, ‘spec_writer’, ‘api_designer’], context: { priority: determinePriority(event), impact_area: determineImpactArea(event) } }; }
function classifyCeremony(event: WebhookEvent): UniversePerspective { // Relational classification const intentMap: Record<string, string> = { ‘issues.opened’: ‘co_creation’, ‘issues.labeled’: ‘intentional_marking’, ‘issue_comment’: ‘dialogue’, ‘pull_request’: ‘offering’ };
| const intent = intentMap[event.event_type] | ‘acknowledgment’; |
return { intent, confidence: 0.7, suggested_flows: [‘relational_auditor’, ‘sacred_pause’, ‘ke_mapper’], context: { seven_generation_impact: assessSevenGenerationImpact(event), relational_implications: assessRelationalImplications(event) } }; }
function classifyStoryEngine(event: WebhookEvent): UniversePerspective { // Narrative classification const narrativeFunctionMap: Record<string, { intent: string; act: number }> = { ‘issues.opened’: { intent: ‘inciting_incident’, act: 1 }, ‘issues.labeled’: { intent: ‘rising_action’, act: 2 }, ‘pull_request.opened’: { intent: ‘turning_point’, act: 2 }, ‘pull_request.merged’: { intent: ‘climax’, act: 3 }, ‘issues.closed’: { intent: ‘resolution’, act: 3 } };
const classification = narrativeFunctionMap[${event.event_type}.${event.action}] ||
narrativeFunctionMap[event.event_type] ||
{ intent: ‘beat’, act: 2 };
return { intent: classification.intent, confidence: 0.85, suggested_flows: [‘narrative_analyzer’, ‘arc_tracker’, ‘beat_generator’], context: { act: classification.act, phase: classification.act === 1 ? ‘setup’ : classification.act === 2 ? ‘confrontation’ : ‘resolution’, throughline: ‘Three worlds must learn to see together’ } }; }
function calculateCoherence( engineer: UniversePerspective, ceremony: UniversePerspective, storyEngine: UniversePerspective ): number { // Simple coherence: average confidence weighted by intent alignment const avgConfidence = (engineer.confidence + ceremony.confidence + storyEngine.confidence) / 3;
// Penalty if intents seem contradictory // (in reality, this would be more sophisticated) return Math.min(1, avgConfidence); }
// Helper functions function determinePriority(event: WebhookEvent): string { const labels = event.payload?.issue?.labels || []; if (labels.some((l: any) => l.name?.includes(‘critical’))) return ‘CRITICAL’; if (labels.some((l: any) => l.name?.includes(‘high’))) return ‘HIGH’; return ‘NORMAL’; }
function determineImpactArea(event: WebhookEvent): string { const title = event.payload?.issue?.title || event.payload?.pull_request?.title || ‘’; if (title.toLowerCase().includes(‘api’)) return ‘API’; if (title.toLowerCase().includes(‘ui’) || title.toLowerCase().includes(‘frontend’)) return ‘UI’; if (title.toLowerCase().includes(‘database’) || title.toLowerCase().includes(‘db’)) return ‘DATABASE’; return ‘GENERAL’; }
function assessSevenGenerationImpact(event: WebhookEvent): string { // Would assess long-term impact in a real implementation const title = event.payload?.issue?.title || ‘’; if (title.toLowerCase().includes(‘architecture’) || title.toLowerCase().includes(‘design’) || title.toLowerCase().includes(‘foundation’)) { return ‘HIGH’; } return ‘MODERATE’; }
function assessRelationalImplications(event: WebhookEvent): string[] { // Would map relationships affected return [‘developer_community’, ‘end_users’]; }
async function handleCreateBeat(event: any): Promise
// Create story beat from event + analysis
const beat = {
id: beat_${Date.now()},
event_id,
timestamp: new Date().toISOString(),
narrative_function: analysis.story_engine.intent,
act: analysis.story_engine.context.act,
perspectives: {
engineer: analysis.engineer.intent,
ceremony: analysis.ceremony.intent,
story_engine: analysis.story_engine.intent
},
lead_universe: analysis.lead_universe,
coherence: analysis.coherence_score,
content: summarizeEvent(raw_payload)
};
// Store beat
await redis.lpush(‘ncp:beats:current’, JSON.stringify(beat));
await redis.hset(ncp:beat:${beat.id}, beat);
return NextResponse.json({ beat_id: beat.id, beat }); }
function summarizeEvent(payload: any): string {
if (payload.issue) {
return Issue #${payload.issue.number}: ${payload.issue.title};
}
if (payload.pull_request) {
return PR #${payload.pull_request.number}: ${payload.pull_request.title};
}
if (payload.commits) {
return Push with ${payload.commits.length} commit(s);
}
return ‘Event processed’;
}
async function handleGetPosition(): Promise
// Determine current act based on beat count and types let currentAct = 1; if (beatCount > 5) currentAct = 2; if (beatCount > 15) currentAct = 3;
return NextResponse.json({ current_act: currentAct, current_phase: currentAct === 1 ? ‘setup’ : currentAct === 2 ? ‘confrontation’ : ‘resolution’, beat_count: beatCount, recent_beats: beats.slice(0, 5).map(b => JSON.parse(b as string)) }); } ```
File: stories/multiverse_3act_2512012121/auto-generator/generate_episode.py (NEW)
```python #!/usr/bin/env python3 “”” Auto-generate NCP episode from webhook event sequence.
Takes a sequence of processed webhook events and generates:
Uses the existing schema and episode templates as foundation. “””
import json import argparse from datetime import datetime from pathlib import Path from typing import List, Dict, Any
EPISODES_DIR = Path(file).parent.parent / “episodes” SCHEMA_PATH = Path(file).parent.parent / “schema” / “ncp-schema.json” TEMPLATE_PATH = EPISODES_DIR / “EPISODE-TEMPLATE.md”
def load_events_from_redis(redis_client, limit: int = 50) -> List[Dict]: “"”Load processed events from Redis””” beats = redis_client.lrange(‘ncp:beats:current’, 0, limit - 1) return [json.loads(b) for b in beats]
def generate_episode_id(episode_number: int, season: int = 1) -> str: “"”Generate episode ID like s01e07””” return f”s{season:02d}e{episode_number:02d}”
def generate_episode_title(events: List[Dict]) -> str: “"”Generate title from event sequence””” # Find the most significant event (inciting incident or climax) for event in events: if event.get(‘narrative_function’) in [‘inciting_incident’, ‘climax’]: return event.get(‘content’, ‘Untitled’).replace(‘#’, ‘’).replace(‘:’, ‘ -‘)[:50] return f”Episode {datetime.now().strftime(‘%Y%m%d’)}”
def generate_ncp_json( episode_id: str, title: str, events: List[Dict] ) -> Dict[str, Any]: “"”Generate NCP JSON structure from events”””
# Group events by perspective
perspectives = []
for universe in ['engineer', 'ceremony', 'story_engine']:
perspective = {
"id": f"{universe}-perspective",
"throughline": get_throughline(universe),
"summary": generate_perspective_summary(events, universe),
"storytelling": generate_perspective_storytelling(events, universe)
}
perspectives.append(perspective)
# Generate story beats from events
storybeats = []
for i, event in enumerate(events):
beat = {
"id": f"beat-{i+1}",
"sequence": i + 1,
"narrative_function": event.get('narrative_function', 'beat'),
"summary": event.get('content', ''),
"tones": [determine_tone(event)],
"perspectives": [
{"perspective_id": f"{event.get('lead_universe', 'story_engine')}-perspective"}
]
}
storybeats.append(beat)
# Generate story points (key moments)
storypoints = []
for i, event in enumerate(events):
if event.get('narrative_function') in ['inciting_incident', 'turning_point', 'climax', 'resolution']:
storypoint = {
"id": f"sp-{event.get('narrative_function', 'moment')}",
"type": event.get('narrative_function'),
"act": event.get('act', 2),
"description": event.get('content', ''),
"timestamp": event.get('timestamp', datetime.now().isoformat())
}
storypoints.append(storypoint)
return {
"schema_version": "1.0",
"story": {
"id": f"multiverse-{episode_id}",
"title": title,
"genre": "Techno-Ceremonial Drama",
"logline": generate_logline(events),
"created_at": datetime.now().isoformat(),
"narratives": [{
"id": episode_id,
"title": f"Episode: {title}",
"subtext": {
"perspectives": perspectives,
"players": get_players(),
"dynamics": get_dynamics(),
"storypoints": storypoints,
"storybeats": storybeats
},
"storytelling": {
"overviews": [],
"moments": generate_moments(events)
}
}]
}
}
def get_throughline(universe: str) -> str: “"”Get throughline for each universe””” throughlines = { “engineer”: “Technical Excellence Through Integration”, “ceremony”: “Sacred Technology Requires Intention”, “story_engine”: “Every Bug Is a Plot Twist” } return throughlines.get(universe, “Unknown Throughline”)
def get_players() -> List[Dict]: “"”Get the character archetypes””” return [ { “id”: “the-builder”, “name”: “Mia”, “archetype”: “The Builder”, “universe”: “ENGINEER”, “characteristics”: [“analytical”, “structural”, “pattern-seeking”] }, { “id”: “the-keeper”, “name”: “Ava8”, “archetype”: “The Keeper”, “universe”: “CEREMONY”, “characteristics”: [“reverent”, “intentional”, “relational”] }, { “id”: “the-weaver”, “name”: “Miette”, “archetype”: “The Weaver”, “universe”: “STORY_ENGINE”, “characteristics”: [“playful”, “narrative-aware”, “integrative”] } ]
def get_dynamics() -> List[Dict]: “"”Get story dynamics””” return [ { “id”: “tension-integration”, “type”: “structural_tension”, “description”: “The gap between disconnected events and meaningful narrative”, “resolution_path”: “Through three-universe processing” }, { “id”: “cross-universe-collaboration”, “type”: “relationship_dynamic”, “description”: “Three universes must share events while maintaining perspectives”, “resolution_path”: “Coherence through divergent interpretation” } ]
def generate_perspective_summary(events: List[Dict], universe: str) -> str: “"”Generate summary for a universe perspective””” relevant_events = [e for e in events if e.get(‘lead_universe’) == universe] if not relevant_events: return f”The {universe} perspective observes from the shadows this episode.” return f”The {universe} perspective processes {len(relevant_events)} key events.”
def generate_perspective_storytelling(events: List[Dict], universe: str) -> str: “"”Generate storytelling note for perspective””” templates = { “engineer”: “In Engineer’s World, every webhook is a potential fracture in the lattice.”, “ceremony”: “Ceremony World processes the same events through relational accountability.”, “story_engine”: “Story Engine World sees the narrative structure emerging from chaos.” } return templates.get(universe, “This perspective continues to evolve.”)
def determine_tone(event: Dict) -> str: “"”Determine emotional tone of event””” function = event.get(‘narrative_function’, ‘’) tones = { ‘inciting_incident’: ‘discovery’, ‘rising_action’: ‘tension’, ‘turning_point’: ‘revelation’, ‘climax’: ‘intensity’, ‘resolution’: ‘satisfaction’ } return tones.get(function, ‘neutral’)
def generate_logline(events: List[Dict]) -> str: “"”Generate episode logline””” inciting = next((e for e in events if e.get(‘narrative_function’) == ‘inciting_incident’), None) if inciting: return f”When {inciting.get(‘content’, ‘an event occurs’)}, the three universes must collaborate.” return “The multiverse continues to process development events through divergent lenses.”
def generate_moments(events: List[Dict]) -> List[Dict]: “"”Generate storytelling moments””” # Group events into scenes moments = [] for i in range(0, len(events), 3): # 3 events per moment moment_events = events[i:i+3] moment = { “id”: f”moment-{i//3 + 1}”, “summary”: f”Moment {i//3 + 1}: Processing events {i+1}-{min(i+3, len(events))}”, “synopsis”: “The three universes interpret the same events differently.”, “setting”: “The Lattice / The Sacred Ground / The Story Engine”, “timing”: moment_events[0].get(‘timestamp’, ‘’) if moment_events else ‘’, “storybeats”: [{“sequence”: j+1, “storybeat_id”: f”beat-{i+j+1}”} for j in range(len(moment_events))] } moments.append(moment) return moments
def generate_markdown(episode_id: str, title: str, events: List[Dict]) -> str: “"”Generate episode markdown””” template = f”””# Episode: {title}
The multiverse continues to process development events, each universe interpreting through its unique lens.
[STORY ENGINE WORLD - The Narrative Lattice]
Events stream in from GitHub. The three universes prepare to interpret.
””” # Add events by act for event in events: if event.get(‘act’) == 1: template += f”- {event.get(‘content’, ‘Event’)} ({event.get(‘lead_universe’, ‘unknown’)} perspective)\n”
template += "\n---\n\n## Act 2: Confrontation\n\n"
for event in events:
if event.get('act') == 2:
template += f"- **{event.get('content', 'Event')}** ({event.get('lead_universe', 'unknown')} perspective)\n"
template += "\n---\n\n## Act 3: Resolution\n\n"
for event in events:
if event.get('act') == 3:
template += f"- **{event.get('content', 'Event')}** ({event.get('lead_universe', 'unknown')} perspective)\n"
template += f""" ---
The journey continues as more events arrive…
def most_common_universe(events: List[Dict]) -> str: “"”Find most common lead universe””” from collections import Counter universes = [e.get(‘lead_universe’, ‘unknown’) for e in events] return Counter(universes).most_common(1)[0][0] if universes else ‘unknown’
def average_coherence(events: List[Dict]) -> float: “"”Calculate average coherence score””” coherences = [e.get(‘coherence’, 0.5) for e in events] return sum(coherences) / len(coherences) if coherences else 0.5
def main(): parser = argparse.ArgumentParser(description=’Generate NCP episode from events’) parser.add_argument(‘–episode-number’, type=int, required=True, help=’Episode number’) parser.add_argument(‘–events-file’, type=str, help=’JSON file with events (if not using Redis)’) parser.add_argument(‘–redis-url’, type=str, help=’Redis URL for event retrieval’) parser.add_argument(‘–output-dir’, type=str, default=str(EPISODES_DIR), help=’Output directory’)
args = parser.parse_args()
# Load events
if args.events_file:
with open(args.events_file) as f:
events = json.load(f)
elif args.redis_url:
import redis
r = redis.from_url(args.redis_url)
events = load_events_from_redis(r)
else:
print("Error: Provide --events-file or --redis-url")
return
if not events:
print("No events to process")
return
# Generate episode
episode_id = generate_episode_id(args.episode_number)
title = generate_episode_title(events)
# Generate outputs
output_dir = Path(args.output_dir)
# Markdown
md_content = generate_markdown(episode_id, title, events)
md_path = output_dir / f"{episode_id}-{title.lower().replace(' ', '-')[:30]}.md"
md_path.write_text(md_content)
print(f"Generated: {md_path}")
# NCP JSON
ncp_content = generate_ncp_json(episode_id, title, events)
ncp_path = output_dir / f"{episode_id}-{title.lower().replace(' ', '-')[:30]}.ncp.json"
with open(ncp_path, 'w') as f:
json.dump(ncp_content, f, indent=2)
print(f"Generated: {ncp_path}")
print(f"\n✅ Episode {episode_id} generated successfully!")
if name == ‘main’: main() ```
narrative_processor.sh hook
/api/narrative-bridge/route.ts
.github-hooks/issues to call narrative processor.github-hooks/push to call narrative processorncp:beats:current - Current story beatsncp:beat:{id} - Individual beat datancp:event:{id} - Event analysis cachencp:state:current - Current narrative positionLast Updated: 2025-12-31
Your Focus: Transform webhooks into narrative intelligence
Success Metric: Automatic episode generation from development events
Inspiration: stories/multiverse_3act_2512012121/ - The vision is already documented!