ariffazil/AGI-multimodal-bridge
skills/AGI-multimodal-bridge/SKILL.md
Multi-modal reasoning bridge — unifies text, image, tabular data, and geospatial evidence into a single reasoning chain. Routes visual analysis through GEOX vision pipeline, tabular data through WEALTH compute, and text through standard LLM reasoning. USE WHEN: "analyze this image + data", "combine visual and textual evidence", "multi-modal prospect evaluation".
$ install --global
skillsauthnpx skillsauth add ariffazil/openclaw-workspace AGI-multimodal-bridgeInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Last scanned: Aug 8, 2026, 3:50 AM391.7s2 files scanned
SKILL.md
- name:
- AGI-multimodal-bridge
- id:
- agi-multimodal-bridge
- risk_tier:
- low
- description:
- Multi-modal reasoning bridge — unifies text, image, tabular data, and
- LLM reasoning. USE WHEN:
- analyze this image + data", "combine visual and textual
- version:
- 1.0.0
- owner:
- AAA
- autonomy_tier:
- T1
AGI-multimodal-bridge
Purpose
Real-world evidence is multi-modal: seismic images, well logs (tabular), geological descriptions (text), financial projections (structured data). This skill bridges modalities into unified reasoning.
Modality Pipeline
- Detect — Identify modalities present in input (text, image, table, geospatial)
- Route — Send each modality to its native processor:
- Text → LLM reasoning (sequential-thinking)
- Image → GEOX vision pipeline (geox_vision) or native vision model
- Table → WEALTH compute pipeline or pandas/numpy analysis
- Geospatial → GEOX map layers (geox_map_layers_list)
- Fuse — Combine processed outputs into unified evidence frame
- Reason — Run cross-modal reasoning chain (observation → signal → narrative)
- Label — Tag each fused claim with epistemic rung and confidence
Fusion Rules
- Cross-modal corroboration raises confidence (two modalities agreeing > one)
- Cross-modal contradiction triggers F2 TRUTH escalation
- Missing modality is noted, not fabricated (F7 HUMILITY)
Floors
- F2 TRUTH: Each modality processed with appropriate fidelity bounds.
- F4 CLARITY: Fused output must be clearer than any single modality.
- F8 GENIUS: Cross-modal synthesis must produce insight > sum of parts.
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