AI Agent Hub
Back to plugins
dsh-clawrouter preview

dsh-clawrouter

admin-security Updated 2026.08.24

Run the following command in DeepSeek Harness:

dsh plugin install BlockRunAI/dsh-clawrouter

Paste the following prompt into your AI chat to install this plugin:

To install in DeepSeek Harness, run dsh plugin install BlockRunAI/dsh-clawrouter from the source repository https://github.com/BlockRunAI/dsh-clawrouter.

About this plugin

dsh-clawrouter addresses the most uncomfortable trade-off in DeepSeek Harness automation: full access can be dangerous, while approving every command by hand is exhausting. It places a stronger model in front of high-risk tool calls and asks it to judge the action as safe, dangerous, or uncertain; the verdict is enforced by the real tool executor, not by prompt-level advice.

The gate is deliberately narrow. It focuses on actions that can cause irreversible damage, such as recursive deletes, raw disk writes, fork bombs, curl-pipe-shell installs, force pushes, hard resets, changes to sensitive files, terraform destroy, and npm publish, while ordinary reads, edits, and builds are left untouched. If the reviewer is unavailable or unsure, the plugin defaults to escalating to a human rather than failing open, and stricter behavior can be configured when needed.

It also registers a BlockRun provider route, allowing the reviewer and many other models to be reached through one wallet with per-request billing and no separate accounts or API keys. This makes it useful for developers who want to run long Harness sessions, test plugins, or automate workflows without accepting the full risk of unrestricted access.

Screenshots

Use Cases

  • Reviews risky shell commands before the agent runs them
  • Reduces manual approvals during long automation sessions
  • Helps prevent accidental deletion while testing plugins or scripts

Best For

  • DeepSeek Harness users worried about full-access risk
  • Developers who want automation without unrestricted command execution
  • Teams or individuals adding a safety layer to agent workflows