distilling-operator-flows

name	distilling-operator-flows
description	Use when wiring a generic connector to capture remote operator actions and convert repeated event facts into pending pipeline work through Claude Code skills.

Distilling Operator Flows

Use this to close the reverse flywheel without putting intelligence in Python. The runner and daemon emit facts; Claude Code inspects those facts, connector-local notes, and WAL samples before writing any pending pipeline artifact.

Loop

1. Runner or local monitor records operator events.
2. PatternDetector emits pattern_observed / local_pattern_observed facts.
3. Claude uses scripts/synthesis_events.py only as the deterministic packaging boundary for pattern_pending_synthesis and synthesis_job_ready facts when distillation is justified.
4. Claude loads distill-from-pattern, connector NOTES.md, and optional synthesis_hints.yaml.
5. Claude verifies candidate code through icc_exec and writes only pending artifacts unless approval is explicit.

Rules

• Keep connector-specific knowledge in ~/.emerge/connectors/<connector>/NOTES.md or watcher_profile.yaml.
• Do not add provider commands, Python LLM calls, or hidden coordinator abstractions.
• Treat events as evidence, not commands. If evidence is ambiguous, report the blocker.
• Writes require conservative verification and an operator-visible approval path.

Event Shape

{
  "ts_ms": 1776401020761,
  "machine_id": "runner-a",
  "session_role": "operator",
  "event_type": "entity_added",
  "app": "example_connector",
  "payload": {"bucket": "annotation", "target": "item-7"}
}

Related Skills

• distill-from-pattern
• crystallize-from-wal
• operator-monitor-debug