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dsh-approval-ai-review

admin-security Updated 2026.09.14

Run the following command in DeepSeek Harness:

dsh plugin install kiiiiile/dsh-approval-ai-review

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

Run dsh plugin install kiiiiile/dsh-approval-ai-review in DeepSeek Harness to install this plugin, source repository: https://github.com/kiiiiile/dsh-approval-ai-review

About this plugin

In DeepSeek Harness permission mode, every tool call can trigger a human confirmation prompt, even for low-risk operations like reading a config file. Approval fatigue slows the workflow down and tempts teams to loosen policies, which paradoxically weakens the guardrail on the operations that truly need oversight.

dsh-approval-ai-review inserts a single auxiliary model call ahead of any human answerer. The tool name, exact call arguments, and the asker reason are sent to the review prompt: an approve verdict resolves the request immediately; an escalate verdict, a timeout, or a malformed response delegates the request down the existing approval waterfall with the review analysis appended to the reason, so the eventual human sees exactly what the operation would do and what it risks. The plugin is inert by default, and the review call is a standalone stream request that consumes zero conversation-transcript tokens and leaves the KV cache untouched.

It is aimed at teams that keep an approval waterfall in their deployment, want to cut down on repetitive manual confirmations, and still want a human in the loop for anything the model does not clear. The plugin never rejects on its own authority, so safe operations get auto-granted while the review effort is spent only where it matters.

Use Cases

  • Auto-grant safe tool calls to eliminate repetitive manual approvals
  • Escalate risky operations to humans with attached risk analysis context
  • Fail-safe fallback to the original approval waterfall on timeout or malformed output

Best For

  • Teams running permission mode with an approval waterfall
  • Operators who want to cut approval fatigue without losing human oversight
  • AI deployment teams balancing efficiency with safety guardrails