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dsh-self-improved

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madage/dsh-self-improved

DeepSeek Harness long-term memory & self-evolving plugin: L0 capture -> L1 memory extraction -> L2 scene grouping -> L3 user persona, auto recall injection + skill synthesis, fully local.

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$ dsh plugin add

15

stars

2

forks

TypeScript

Language

MIT

License

2026-08-15

Created

2026-08-15

Last push

Use dsh-self-improved in DeepSeek Harness with the documented install steps and limits.

DSH integration

Native runtime

Author-claimed

Safety audit

Unaudited

Last verified

2026-11-06

License

MIT

01What can it help you accomplish?

  • DeepSeek Harness long-term memory & self-evolving plugin: L0 capture -> L1 memory extraction -> L2 scene grouping -> L3 user persona, auto recall injection + skill synthesis, fully local.

    **Long-term memory & self-evolving plugin** for DeepSeek Harness (fully local).

    DeepSeek Harness users who need this workflow

02How to install into DeepSeek Harness

Installation steps

  1. 01

    > **Since 0.1.1**: the package declares `dsh.bundle`, so **`dsh plugin add` / plugin-marketplace one-click install auto-mounts it** (dsh registers it as a profile layer automatically) — **no manual `c

    $ dsh plugin add

Verify the integration

  • After installation, confirm the plugin UI or command described in the README is available.

03DSH integration and capability boundaries

DSH integrationNative runtime

DSH plugin bundle / host integration

  • Documented workflow

    A task or request in DSH→**Long-term memory & self-evolving plugin** for DeepSeek Harness (fully local).

  • Plugin configuration

    The settings or command options documented by the author→Configured plugin behavior in the DSH host

04Who is it for? When not to use it?

Good for

  • DeepSeek Harness users who need this workflow

Not for

  • The architecture follows the four-layer memory pyramid of TencentDB Agent Memory (L0 capture → L1 extraction → L2 scene grouping → L3 persona), but **reuses DSH-native services** (`ctx.llm` / `session

05Compatibility, maintenance and safety notes

  • The architecture follows the four-layer memory pyramid of TencentDB Agent Memory (L0 capture → L1 extraction → L2 scene grouping → L3 persona), but **reuses DSH-native services** (`ctx.llm` / `session
  • The plugin depends on the DSH host and the prerequisites documented by its author.
2026-08-152026-08-15Not specified by the author

active

06Frequently asked questions

What does this plugin do?

It provides the DSH workflow described in the README.

How do I install it?

Follow the README install command or steps shown on this page.

What should I check first?

Check the documented prerequisites and constraints before enabling it.

08Data and sources

  • Author-claimedgithub.com4f134c9a93db…

    # dsh-self-improved

This page is generated from the project’s public documentation, repository metadata and a structured parse of DSH Plugins; last verified on 2026-11-06. Found an error? Submit a correction.

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