OpenExec Skill: Deterministic Execution Boundary for OpenClaw Agents
An OpenClaw Runner-review candidate for separating agent proposals from approved execution, with replay protection, receipts,...
Agent Audit is a community OpenClaw skill candidate for operators who run multiple agents, scheduled jobs, or mixed model providers and need a cost review before usage quietly compounds.
The skill page describes a read-only audit flow that scans OpenClaw configuration, cron history, session history, and model assignments. Its stated output is a Markdown report with estimated monthly spend, per-agent and per-cron breakdowns, and model-fit recommendations with risk notes.
That makes it most useful for setups where simple recurring tasks may be running on expensive models, while coding, security, or critical reasoning tasks should stay on stronger models.
Use this as a candidate if you manage OpenClaw on a VPS, Raspberry Pi, or always-on workstation and already have several agents or scheduled automations. It is less useful for a single-agent install with little run history.
The ClawHub page lists openclaw skills install agent-audit and shows a Python entrypoint under scripts/audit.py. Review the SKILL.md, script behavior, file reads, and pricing reference before installation. Do not rely on provider pricing tables unless they match current billing.
LinkLoot has not run this skill. Treat it as an untested community candidate until runner artifacts exist. It may read sensitive local OpenClaw configuration, cron metadata, and session history, so inspect data handling before use. Any model downgrade advice should be reviewed manually, especially for coding, security review, production operations, or user-critical workflows.
agent-audit under Coding Agents & IDEs.
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