AI agent swarm: how to run OpenClaw Swarm without a coordination mess
AI agent swarm workflows can speed up independent work, but only when concurrency, permissions, result schemas, and failure handling are explicit.
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Agent Governance
11 articles connected to this topic.
OpenClaw personal skill libraries: private skills on a shared Gateway
OpenClaw personal skill libraries let each signed-in teammate keep private skills on a shared Gateway, import them from ZIP, and share or hand off ownership without host access.
OpenClaw skills: how to avoid skill sprawl
OpenClaw skills stay useful when each one has a clear owner, trigger, and review date. Use this practical system to prune overlap before your agent becomes harder to trust.
OpenClaw skills: choose per-agent, shared, or workspace scope
OpenClaw skills can live in a workspace, a personal agent directory, or a shared managed directory. Learn how precedence and allowlists shape the right scope.
AI agent hook policies in OpenClaw 2026.6.10: keep approvals trusted after composition
AI agent hook policies need to survive plugin composition, retries, and channel handoffs. OpenClaw 2026.6.10 keeps trusted tool policies attached to approval-sensitive flows.
AI agent search tool governance: why key-free providers should stay opt-in
AI agent search tool governance keeps free and local search providers useful without letting hidden defaults shape citations, storage, cost, and operator trust.
AI agent configuration management needs safer config patches
AI agent configuration management fails when patches widen silently. OpenClaw 2026.6.6 uses explicit array replacement and consent-bound paths to reduce config drift.
Chain-of-thought leakage in AI agents: keep reasoning out of user replies
Chain-of-thought leakage is a production risk for AI agents. Learn where reasoning traces escape, why channel adapters matter, and how OpenClaw reduces exposure.
AI agent workboard: visible handoffs for multi-agent runs
AI agent workboard explains how visible handoffs, task comments, and review points keep multi-agent orchestration debuggable instead of hidden agent chatter.
AI agent security boundaries in OpenClaw 2026.5.27
AI agent security boundaries in OpenClaw 2026.5.27 separate untrusted prompts, tool execution, network exposure and approvals so agent failures stay contained.
AI agent policy checks in OpenClaw 2026.5.20: what changed and how to use them
AI agent policy checks in OpenClaw 2026.5.20 add a practical control layer for channels, approvals, sandbox visibility, and workspace repair.