Put approval gates and audit-ready policy checks between agents and external actions with DashClaw
Use DashClaw to intercept agent actions before they hit external systems, require approval or policy evaluation, and keep replayable decision evidence for later review.
What it does
Put approval gates and audit-ready policy checks between agents and external actions with DashClaw
Use DashClaw to intercept agent actions before they hit external systems, require approval or policy evaluation, and keep replayable decision evidence for later review.
Prerequisites
DashClaw service plus a supported agent framework or MCP-capable client
Installation
Use the upstream install or setup path that matches your environment:
- npx dashclaw-demo
- npm install dashclaw # or: pip install dashclaw
Requirements and caveats from upstream:
- Python uses the same shape with snake_case. Full reference: sdk/README.md. Step-by-step walkthrough: QUICK-START.md.
- Node SDK reference: canonical reference for the dashclaw npm package.
- Python SDK reference: same surface, snake_case.
Basic usage or getting-started notes:
- <p><sub>Plugs into the agents you already run: Claude Code, Codex, Hermes Agent, OpenClaw, Claude Desktop, and Claude Managed Agents. Framework integrations for LangChain, CrewAI, AutoGen, LangGraph, and OpenAI Agents...
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| Enforce | Declarative policies (risk thresholds, deploy gates, capability access rules, semantic checks) run on every action. |
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10-second demo
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Extracted from upstream docs: https://raw.githubusercontent.com/ucsandman/DashClaw/HEAD/README.md
Documentation
Source
Capabilities
Install
Quality
deterministic score 0.45 from registry signals: · indexed on github topic:agent-skills · 8 github stars · SKILL.md body (1,675 chars)