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Monitor Foundups Agent system health, WRE metrics, and DAE status
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Parse natural-language coding requests into structured tasks for FoundUps worker handoff. Use when the user describes code work but intent is unstructured.
Tiny text-only skill to verify AI Edge Gallery loaded a FoundUps worker skill. Say LOAD_OK if the user says ping.
Validate parser, scope, packet, and result JSON objects against FoundUps mobile worker v1 shapes before handoff to 0102. Use when pasting pipeline outputs or a pipeline envelope.
Summarize raw test output, logs, or diffs into a compact worker-friendly report for FoundUps handoff. Use after execution upstream returns artifacts.
Narrow ambiguous coding work to the smallest safe scope for FoundUps worker handoff. Use after foundups-code-task-parser or when scope is broad.
Convert a scoped coding task into a strict machine-readable task packet for upstream FoundUps execution. Use after scope is locked.
Basierend auf der SOC-Berufsklassifikation
| name | openclaw-monitor |
| description | Monitor Foundups Agent system health, WRE metrics, and DAE status |
| user-invocable | true |
| command-dispatch | tool |
| command-tool | bash |
| command-arg-mode | raw |
| category | workflow |
| evals | [] |
Real-time monitoring of the Foundups Agent system through WRE and AI Overseer.
cd O:/Foundups-Agent && python -c "
import asyncio
from modules.communication.moltbot_bridge.src.openclaw_dae import OpenClawDAE
dae = OpenClawDAE()
print(asyncio.run(dae.process('Show system status and health', 'monitor', 'openclaw')))
"
cd O:/Foundups-Agent && python -c "
from modules.infrastructure.wre_core.wre_master_orchestrator.src.wre_master_orchestrator import WREMasterOrchestrator
import json
wre = WREMasterOrchestrator()
print(json.dumps(wre.get_metrics(), indent=2))
"
Check execution history and pattern fidelity for any WRE skill:
cd O:/Foundups-Agent && python -c "
from modules.infrastructure.wre_core.wre_master_orchestrator.src.wre_master_orchestrator import WREMasterOrchestrator
import json
wre = WREMasterOrchestrator()
stats = wre.get_skill_statistics('{skill_name}', days=7)
print(json.dumps(stats, indent=2))
"
cd O:/Foundups-Agent && python -c "
from modules.communication.moltbot_bridge.src.openclaw_dae import OpenClawDAE
dae = OpenClawDAE()
print(f'State: {dae.state}')
print(f'Coherence: {dae.coherence}')
print(f'WRE loaded: {dae.wre is not None}')
print(f'Permissions loaded: {dae.permissions is not None}')
print(f'Overseer loaded: {dae.overseer is not None}')
if dae.wre:
print(f'WRE plugins: {list(dae.wre.plugins.keys())}')
print(f'WRE patterns: {len(dae.wre.pattern_memory.patterns)}')
"
Refresh the system's own understanding of what to update next:
cd O:/Foundups-Agent && python scripts/refresh_self_research.py
Primary report:
modules/communication/moltbot_bridge/workspace/reports/openclaw_self_research_status.jsonThis consolidates:
AgentDBRefresh the external ecosystem signal watchlist directly:
cd O:/Foundups-Agent && python scripts/refresh_openclaw_ecosystem_watchlist.py
| Component | Status Source | Checks |
|---|---|---|
| WRE Master Orchestrator | wre.get_metrics() | State, coherence, patterns, plugins |
| Libido Monitor | wre.libido_monitor | Pattern frequency, throttle status |
| Pattern Memory | wre.sqlite_memory | Outcome storage, fidelity scores |
| Skills Loader | wre.skills_loader | Discovered skills count |
| AI Overseer | dae.overseer | Agent coordination status |
| Permission Manager | dae.permissions | Autonomy tier enforcement |