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dsh-yolo-mode

LLM-powered auto-approval and policy plugin for DeepSeek Harness sandbox escalations with fail-closed safety.

Developer ToolsSecurity & PolicyRemote Execution
3GitHub Stars0ForksUpdated2026-10-19

Install

$ dsh plugin --profile web add dsh-yolo-mode

Plugin Overview & Capabilities

AI-assisted organization based on the public repository snapshot. The content must be grounded in source evidence and does not replace compatibility or security verification.

source-grounded
dsh-yolo-mode is a DeepSeek Harness plugin that intercepts sandbox escalation requests in workspace-write sessions when approval is set to ask. It leverages an LLM judge to automatically evaluate escalation requests across built-in presets (off, strict, balanced, permissive, yolo, custom) and granular per-tool permission levels, enforcing fail-closed fallbacks and providing interactive web status chips, logs, and settings UI.

Key Capabilities

  • Intercepts sandbox escalation requests and delegates decisions to an LLM judge based on configurable presets
  • Provides fine-grained per-tool and per-target permission levels (allow, judge, delegate, deny)
  • Ensures fail-closed security by defaulting timeouts, invalid outputs, or errors to human delegation or denial
  • Offers web UI components including an input status chip, decision statistics popup, and runtime settings page
  • Maintains local JSONL audit logs recording tool names, target modes, rationale, decisions, and error codes

Useful For

  • Automating repetitive approval prompts during autonomous coding sessions while maintaining granular control
  • Enforcing strict or balanced sandbox privilege escalation policies for multi-tool agent workflows
  • Auditing and inspecting LLM agent permission escalation requests via structured JSONL logs and web UI analytics

Who It Fits

  • Developers seeking hands-free DeepSeek Harness agent execution without completely bypassing sandbox security
  • Teams requiring auditable, tiered sandbox escalation controls and safety fail-safes for autonomous agents

Documented Limitations

  • High-reasoning LLMs require larger judge token budgets (judge.maxTokens) to prevent premature truncation and BAD_OUTPUT fallback errors
  • Overlaps functionally with DeepSeek Harness experimental native auto-review (@deepseek-ai/dsh-experimental-auto-review)
  • Author notes the plugin may be deprecated in the future in favor of official upstream auto-review capabilities

DSH Compatibility

Version-specific runtime evidence collected by DSH Plugin. A missing result means we have not tested that combination yet.

Not tested yetNo runtime compatibility tests have been published yet.

Security Signals

Objective signals discovered from package metadata and source inspection. These are not a guarantee that a plugin is safe.

Dependency Counts

package.json declares 0 runtime, 6 development, 9 peer, and 0 optional dependencies.

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Dsh Bundle Declared

package.json declares DSH bundle metadata.

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License Declared

GitHub reports the repository license as MIT.

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Package Manifest Available

A root package.json was captured and can be inspected by the registry.

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Source Available

Public GitHub source metadata is available for this registry snapshot.

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Source & Registry Notes

Public provenance, Registry classification, and the latest source check for this entry, kept separate from runtime verification.

Source repository
SeverusZh/dsh-yolo-mode
Registry source
GitHub · dsh-plugin topic
Registry classification
Plugin
Source checked
a83f46a · 2026-10-22

This project is independently indexed from public source information. DSH Plugin is not affiliated with DeepSeek or the plugin author. Always check the author repository before installation.

Repository Activity

GitHub stars
3GitHub stars
Forks
0
Open issues
0
Last commit
2026-10-19
Last release
2026-10-19
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