dsh-memory-canvas

dsh-memory-canvas

DeepSeek Harness plugin. Offload bulky tool logs to refs/*.md. Keep a Mermaid canvas in context. Recall by node_id. Zero daemon.

CAUTION: don't pip the wrong dsh. Official CLI: npx @deepseek-ai/dsh web. The PyPI package deepseek-harness-cli is a different tool (dsh doctor / dsh chat).

GitHub topic: dsh-plugin. Chinese: README.zh.md

Demo (no dsh)

node demo.mjs

Writes .dsh-memory/refs/{id}.md, prints the canvas, recalls by id, and asserts the body matches.

Install into a profile

This package is plain JavaScript. There is no prepare or build step, so a git install does not need allowBuilds.

dsh plugin --profile web add github:guobinmengxiang-rgb/dsh-memory-canvas

Check the composed layer without booting:

dsh --profile web --dump-config

You should see a dsh-memory-canvas layer. Then start the profile as usual.

Official CLI is @deepseek-ai/dsh (today 0.1.0-rc.6).

Tools

The agent must call these tools. This plugin does not auto-intercept tool logs.

Tool	Params	Result
memory_offload	title, body (required)	short id, path, canvas updated
memory_recall	id (required)	stored body (truncated at 8k with a note)
memory_canvas	none	Mermaid markdown of the task canvas

Storage (default): <cwd>/.dsh-memory/canvas.md and <cwd>/.dsh-memory/refs/{id}.md. Override root with DSH_MEMORY_DIR.

Canvas nodes use a 24-character title. Full text lives in refs/.

What this is not

• Not TencentDB Agent Memory (not their L0-L3 persona pipeline)
• Not OpenClaw
• Not a vector DB
• Not Yiipu/dsh-agentmemory (that one needs a daemon on :3111)

Inspired by Tencent's short-term symbolic memory (MIT idea, our code): refs + Mermaid canvas + node_id.

Honest limits

• DeepSeek Harness is a developer preview: THERE WILL BE COMPATIBILITY-BREAKING CHANGES.
• The plugin runs on your machine.
• This bundle cordis.patch.yml uses the package name dsh-memory-canvas, not a filesystem path.

Official docs and related

• Your first plugin: https://deepseek-harness.github.io/deepseek-harness/en/develop/basic/
• Package and install a plugin: https://deepseek-harness.github.io/deepseek-harness/en/develop/basic/publish
• Cordis: https://github.com/cordiverse/cordis
• Sister plugin: https://github.com/guobinmengxiang-rgb/dsh-xhs-note
• Course: https://github.com/guobinmengxiang-rgb/dsh-getting-started
• Awesome list: https://github.com/guobinmengxiang-rgb/awesome-dsh

License

MIT (c) 2026 国彬 张