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Monitor Foundups Agent system health, WRE metrics, and DAE status
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
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.
Baseado na classificação ocupacional SOC
| 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 |