skills/ARCHIVE/HERMES-multi-modal-bridge/SKILL.md
IO boundary protocol for Hermes ↔ 333-AGI multi-modal signal routing. Ingests vision/audio signals from Hermes' creative/media surface and routes them as structured evidence payloads into the reasoning layer. USE WHEN: Hermes encounters an image, audio, or video that requires reasoning beyond creative routing.
npx skillsauth add ariffazil/openclaw-workspace HERMES-multi-modal-bridgeInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Hermes ingests. AGI reasons. APEX judges.
Hermes is the human-facing creative surface — it encounters images, audio, voice, video. Hermes does NOT perform deep reasoning on these signals. It classifies, extracts, and routes them as governed evidence payloads to the reasoning layer (333-AGI).
When Hermes receives multi-modal content:
ingest_classification:
modality: IMAGE | AUDIO | VIDEO | VOICE | MIXED
source: TELEGRAM | API | UPLOAD | URL
requires_reasoning: true | false # Set true if content needs interpretation
requires_creative_routing: true | false # Set true for text-to-image, TTS, etc.
For content requiring reasoning:
evidence_payload:
bridge_id: "mmb_<timestamp>_<random6>"
modality: IMAGE
extracted:
perceptual_inventory:
- element: "text visible in image"
confidence: high
- element: "chart showing decline from Q1 to Q3"
confidence: medium
transcription: "<text extracted from audio/OCR>"
metadata:
dimensions: "1920x1080"
format: "image/png"
duration_seconds: null
reasoning_request:
intent: "Analyze this seismic section for structural traps"
domain: geox
urgency: standard
provenance:
ingested_by: "hermes-asi"
ingested_at: "2026-07-13T02:20:00Z"
source: "telegram_message_id:8471"
The payload routes through AAA A2A gateway:
Hermes → AAA gateway (port 3001)
→ arif_route(intent="analyze seismic section")
→ 333-AGI (structured evidence in A2A task)
→ arif_judge if decision required
→ Hermes (response payload back to human)
IMAGE → Reasoning:
{
"bridge_id": "mmb_20260713_0215_a3f2c1",
"modality": "image",
"agI_verdict": "STRUCTURAL_CLOSURE_DETECTED",
"confidence": 0.78,
"evidence": [
{"claim": "Anticlinal four-way dip closure visible in inline 4200", "label": "OBS", "confidence": 0.85},
{"claim": "Fault seal risk on eastern flank", "label": "DER", "confidence": 0.60}
],
"requires_human_review": true,
"routed_to": "geox_seismic_compute"
}
AUDIO → Reasoning:
{
"bridge_id": "mmb_20260713_0220_b4d3e2",
"modality": "audio",
"transcription": "I need the Q2 production forecast for Bekok field by tomorrow",
"agI_decomposition": {
"task": "Generate Q2 production forecast",
"domain": "geox",
"subtasks": ["fetch_bekok_production_history", "decline_curve_analysis", "generate_forecast_chart"],
"estimated_tools": ["geox_well_ingest", "geox_petrophysics", "FORGE-chart"]
},
"urgency": "high",
"deadline": "2026-07-14T00:00:00+08:00"
}
When content only needs creative/media routing (no reasoning):
creative_route:
intent: "Generate image of Malay Basin cross-section"
route: "minimax-media → text-to-image"
payload: "{prompt, style, dimensions}"
# Does NOT go through 333-AGI reasoning layer
| F | Obligation |
|---|-----------|
| F2 TRUTH | Perceptual inventory labeled with confidence per element |
| F4 CLARITY | Structured A2A JSON, never raw binary over the bridge |
| F6 MARUAH | Never describe humans in images without consent context |
| F11 AUDIT | Every bridge has bridge_id for traceability |
| F13 SOVEREIGN | Human-in-the-loop for any image of people or sensitive content |
Forged: 2026-07-13 by FORGE (000Ω) under F13 SOVEREIGN directive DITEMPA BUKAN DIBERI
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