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dsh-shadow-mind

Workflow Updated 2026.08.25

Run the following command in DeepSeek Harness:

dsh plugin install winterhuan/dsh-shadow-mind

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

Run dsh plugin install winterhuan/dsh-shadow-mind to add the plugin to your DSH profile; source code is available at https://github.com/winterhuan/dsh-shadow-mind

About this plugin

In DSH (DeepSeek Harness), the main agent typically handles all reasoning and execution in isolation, with no external perspective to cross-check conclusions or surface blind spots. dsh-shadow-mind introduces a set of "Shadow Mind" agents that are randomly activated after each main-agent turn by a probabilistic heartbeat scheduler. Each shadow carries its own responsibility description, tool allowlist, and per-run timeout, working in parallel to perform fact-checking, independent review, and multi-path cognitive exploration.

Core mechanics include: every shadow receives a sanitized main-session trajectory and an explicit tool allowlist (read-only by default); runs that exceed their timeout are interrupted and their slots released; tool-call arguments are redacted before forwarding so credentials never leak; and finished subagents are cleaned up automatically at epoch boundaries. Users can inspect state, probe a shadow manually, or pause/resume the system via /shadow commands, and can programmatically create, update, enable, or disable shadow definitions through model-callable management tools. Global configuration stays in sync across the DSH web settings panel, write_shadow_config tool calls, and manual edits to settings.yaml.

Ideal for DSH users tackling long-document analysis, multi-step code review, or technical design validation where multi-perspective cross-checking adds real value. It also suits workflow builders who want a composable, configurable cognitive layer attached to their main agent. The plugin is currently a functional prototype with core scheduling, restricted agents, timeout enforcement, and lifecycle management working end-to-end.

Use Cases

  • After generating a long research report, shadow minds independently cross-verify key conclusions automatically
  • In multi-step code review, read-only shadow agents run in parallel to surface logic flaws and edge cases
  • During technical design validation, multiple shadows explore in parallel from different responsibilities to reduce single-perspective blind spots

Best For

  • Developers handling complex reasoning tasks in DSH who need multi-perspective cross-validation
  • Workflow builders who want a configurable, composable cognitive layer attached to their main agent
  • DSH plugin authors interested in multi-agent parallel scheduling and restricted-tool isolation patterns