DeepSeek Harness plugin

dsh-plugin-lifensame

Global memory plugin for the DeepSeek Harness: persistent cross-session memories, automatic per-task recall, and model-facing add/search/list/delete/summarize tools

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Source facts

Repository
lifensame/dsh-plugin
Latest update
Aug 15, 2026
Category
Tools & Capabilities
GitHub stars
3
Format
plugin
Catalog evidence
Upstream dsh.bundle evidence
Evidence path
package.json#dsh.bundle
Checked against
0.1.0-rc.8
Upstream check date
2026-08-20

This evidence comes from the upstream catalog. This site has not installed, run, or security-reviewed the plugin.

Install

Start with a prompt that asks an agent to review the GitHub repository and source. Switch to the command if you want to install it yourself.

Copy this prompt into DSH, Codex, or another agent and ask it to review the GitHub repository and source first.

Do not install or run any commands yet. Read this plugin's GitHub repository, README, and relevant source code. Then answer the questions below clearly and directly so I can decide whether it fits my needs:

1. What is this plugin, and what problem does it solve?
2. Who is it for, and what are its typical use cases?
3. How is it used after installation? Include one minimal example.
4. What known limitations or privacy, security, compatibility, or maintenance risks does it have?
5. Give a clear recommendation: recommend, conditionally recommend, or do not recommend, with reasons.

Distinguish statements documented by the repository, inferences from source code, and unknowns. If evidence is insufficient, say so explicitly. Do not guess or simply repeat the README.

GitHub: https://github.com/lifensame/dsh-plugin
Plugin: dsh-plugin-lifensame
Author: lifensame

Check the source files

Read the README and other files from this plugin directory before installing.

File explorer4 files
README.mdSource · read only
README language

dsh-memory

Global memory plugin for the DeepSeek Harness (dsh). It gives every agent a persistent, cross-session long-term memory: durable facts, user preferences, and decisions that survive across sessions, projects, and workspaces — and it automatically recalls them into every task.

![Q版 DeepSeek 记忆吉祥物](assets/q-version-deepseek-memory.jpg)

> 📖 Full usage tutorial (install, verify, daily use, config, FAQ): [docs/tutorial.md](./docs/tutorial.md) (中文)

> 中文说明见 README.zh.md

What it does

FeatureHow it works
Global storeMemories are plain Markdown files under $DSH_HOME/memory/*.md (shared by every session, not tied to any workspace).
Automatic recallThe memory context is injected into every agent step, so every task starts with your memories already loaded.
Automatic inputThe agent saves memories itself through tools — no manual file editing.
Auto-summarizememory_summarize distills a long input (or a recap of the conversation) into a compact memory using the language model.
Human commands/memory lists (or searches) memories from the chat UI.

Model-facing tools

  • memory_add — save a durable fact / preference / decision. Reusing the same title (or id) updates the existing memory.
  • memory_search — keyword search over titles, tags, and body.
  • memory_list — list all memories (optionally filtered by tag).
  • memory_delete — forget a memory by id.
  • memory_summarize — distill text into a compact memory via the LLM, then save it.

The standing injected instruction also tells the agent to proactively keep memory current (save new durable facts, update stale ones, avoid duplicates).

Install

With the GitHub CLI and pnpm installed, add the plugin to a profile:

# git source (this repository)
dsh plugin --profile web add github:lifensame/dsh-plugin

# or, from a local checkout
dsh plugin --profile web add <path/to/dsh-plugin>

# or, once published, from npm
dsh plugin --profile web add dsh-memory

Then restart the profile. The first time you add it, pnpm installs the package and dsh reconciles it into the profile's bundle list automatically.

How memories are stored

Each memory is one Markdown file with YAML frontmatter:

---
id: favorite-color-abc123
title: Favorite color
tags: [prefs]
importance: high
created: 2026-01-01T00:00:00.000Z
updated: 2026-01-02T00:00:00.000Z
---
The user's favorite color is blue.

They live under $DSH_HOME/memory (~/.dsh/memory by default), so you can also edit them by hand or put them under version control.

Configuration

All options are optional; the values below are the defaults.

# profile cordis.patch.yml — the dsh-memory row
- id: memory
  name: dsh-memory
  config:
    memoryDir: memory              # directory (relative to $DSH_HOME) holding the .md files
    maxInjectedBytes: 16384        # UTF-8 budget for the auto-injected memory context
    searchDefaultLimit: 5          # default result count for memory_search
    summarizeProvider: ''          # explicit LLM provider route for memory_summarize (empty = default model)
    summarizeModel: ''             # explicit LLM model id, paired with summarizeProvider
    summarizeMaxInputBytes: 24576  # max input size memory_summarize accepts
    summarizeMaxOutputTokens: 512  # max tokens for the summarization call
    summarizeTimeoutMs: 60000      # timeout for the summarization call

Q-version logo

A ready-to-use prompt for generating a chibi (Q版) DeepSeek-memory mascot is in [docs/image-prompt.md](./docs/image-prompt.md).

License

MIT