hypothesis-proximity-updatelisted

# hypothesis-proximity-update Goal: - Update hypothesis proximity state by invoking the canonical embedding bridge for one hypothesis. Inputs: - optional existing `state/PROXIMITY_GRAPH.json` - target `hypothesis_id` - run-frozen embedding provider settings from `state/RESOLVED_RUN_CONFIG.json` Outputs: - updated `state/proximity_receipts/<hypothesis_id>.json` - updated `state/PROXIMITY_STATUS.json` - updated in-memory `ProximityGraphContract` - updated `state/PROXIMITY_GRAPH.json` when the provider returns a valid embedding - updated `state/PIPELINE_STATE.json` - updated `state/CURRENT_STAGE.json` Context Loading: - Open `skills/shared-references/schema-index.md`. - Read `packages/agent_contracts/state.py` and confirm the exact `ProximityGraphContract` shape before writing `state/PROXIMITY_GRAPH.json`. - Read `packages/agent_contracts/proximity.py` and confirm the proximity receipt and status schemas before interpreting provider outcomes. - Read `packages/agent_contracts/pipeline_runtime.py` before updating `state/PIPELINE_STATE.json` or `state/CURRENT_STAGE.json`. - Load the current proximity graph if it exists. If it does not exist yet, start from an empty `ProximityGraphContract`. - Treat embedding generation as a bridge/tool concern. Host agents must not generate, infer, paste, or hand-write numeric embeddings in prompt output. - Do not skip this skill merely because no embedding vector is already present in the execution context. Execution Contract: - This ski