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.
Pending human review — the facts below come from the source repository.
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.
Users who want this capability in DSH; check the source and docs before installing.
dsh plugin --profile web add github:madage/dsh-self-improved No supported platforms were declared.
.gitignore). ## What it is Adds the two missing capabilities to DSH — "cross-session memory + self-evolution": - Memory: automatically distills key points from conversations (facts / preferences / events / instructions) into a local memory store; before each new turn, relevant memories are injected to the model — the AI "remembers you". - Self-evolution: memories are consolidated, decayed and corrected; successful workflows can be distilled into reusable skills; the user persona keeps evolving with conversations. 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 events / agent/pre-step injection / dsh-skill / storageDomain) with a fully local SQLite store (FTS5 + sqlite-vec). No data is uploaded anywhere. ## Roadmap | Milestone | Scope | Status | |---|---|---| | M0 | Probe: event capture / recall injection / tool registration / settings namespace | ✅ Verified (isolated headless) | | M1 | Memory store: SQLite + FTS5 + jieba + sqlite-vec; L0 capture to disk; memory/search tools | ✅ Verified (unit + headless integration) | | M2 | Extraction pipeline: ctx.llm L1 extraction + strict JSON validation/fallback + dedup + throttled pump | ✅ Unit-tested; running in production | | M3 | Recall injection: agent/pre-step injection + keyword/vector/hybrid retrieval (RRF) | ✅ Unit-tested + end-to-end verified | | M4 | Self-evolution: L2/L3 consolidation (scenes + versioned persona), decay, correct/forget tools, skill synthesis → dsh-skill | ✅ Unit-tested; synthesized skills in production | | M5 | UI/ops: settings panel (auto-rendered) + hot runtime toggles + /memory command + memory browser | ✅ Complete, deployed to web profile | | M6 | Growth governance (caps/cleanup) + scheduling (nightly review / free maintenance / startup backfill) | ✅ Complete: governance caps, nightly review (default 22:00), 15-min loop is maintenance-only, master switch stops all timers | ## Installation > 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 cordis.patch.yml edits needed. Just restart dsh after installing. ### Option 1: npm (recommended; same as marketplace one-click) bash dsh plugin --profile web add dsh-self-improved # or find dsh-self-improved in the plugin marketplace and click install # restart dsh — it auto-mounts ### Option 2: from GitHub (source snapshot, prepare builds lib/ automatically) bash # 1) One-time environment prep (only if you hit store mismatch / blocked build): # - point the store back to the directory consistent with node_modules: # pnpm config set store-dir E:\dshPro\.pnpm-store --global # or set store-dir=... in a profile-level .npmrc # - allow prepare builds for git-installed packages (pnpm >= 10 blocks by default); in pnpm-workspace.yaml: # allowBuilds: # dsh-self-improved: true # 2) Install (dsh plugin forwards to pnpm in the profile; github:owner/repo fetches the snapshot and runs prepare=tsc) dsh plugin --profile web add github:madage/dsh-self-improved # 3) Restart dsh (auto-mounts since 0.1.1; if it still doesn't load, add the manual insert below) > Manual mount (legacy versions or special layouts only): add to the insert list of $DSH_HOME/profiles/web/cordis.patch.yml: > yaml > - insert: > - id: dsh-self-improved > name: dsh-self-improved > ### Option 3: local development (file: link) bash # build, then copy lib/ + client.js + package.json into # $DSH_HOME/profiles/web/node_modules/dsh-self-improved/ # add "dsh-self-improved": "file:node_modules/dsh-self-improved" to package.json dependencies # add the cordis.patch.yml insert (above) → restart ### ⚠️ Install notice: peerDependencies double-instance pitfall (located & fixed) Symptom: after install, new sessions work but resuming an old session errors — deployment:persona already registered, with a hint "register through that agent's agent.ctx instead". Root cause (not a plugin bug): pnpm's default autoInstallPeers installs the plugin's @deepseek-ai/* peerDependencies as physical copies inside the profile's node_modules, creating two independent module instances of the same package as the ones embedded in the dsh main install (e.g. dsh-scope). DSH's scoping (preset/persona layers) binds identity via Symbol("dsh.scope"); with two instances the persona registration lands in the global layer and collides with the host's deployment:persona → resume fails. New sessions happen to succeed because the global layer is not yet occupied on first registration. Fix (verified): 1. Replace the redundant @deepseek-ai/* physical copies in the profile with symlinks to the packages embedded in the dsh main install (dsh's self-healing layout $DSH_HOME/profiles/node_modules); 2. Set auto-install-peers=false in a profile-level .npmrc (or turn off autoInstallPeers in pnpm-workspace.yaml). Note for users (keep when publishing): > dsh-self-improved's peerDependencies may be auto-installed as physical copies in the profile; use the dsh self-healing symlink layout, or set auto-install-peers=false in the profile's .npmrc. ### ⚠️ Install notice: duplicate loader entry id (bundle re-mount, instant boot crash) Symptom: dsh fails to start (window flashes and closes), and dsh --profile web --dump-config shows the same entry id twice. Root cause: packages declaring dsh.bundle (this plugin since 0.1.1, dsh-plugin-marketplace, etc.) are automatically added to dsh.profile.bundles and their bundled cordis.patch.yml inserts one entry; if the profile-level cordis.patch.yml also manually inserts the same id → the loader throws duplicate loader entry id at boot. Fix (verified): reset the profile-level cordis.patch.yml to [] — bundle assembly is fully owned by dsh.profile.bundles; do not manually insert bundle plugins at the profile layer. Debug tip: if dsh crashes at startup, run dsh --profile web --dump-config and count each entry id; more than one occurrence is this problem. ## Configuration yaml # $DSH_HOME/settings.yaml dsh-self-improved: enabled: true modules: capture: true extract: true consolidate: true evolve: true recall: true tools: true review: enabled: true # nightly review (one full evolution per day) time: "22:00" # HH:MM, 24h Notes: - Master switch off = plugin fully dormant: all background timers stop (15-min maintenance loop / nightly review / startup backfill), /memory and memory tools are unregistered; stored memories are kept and everything resumes when re-enabled. - Scheduling: the 15-minute loop only does extraction + free maintenance (decay/governance, no LLM cost); full evolution (scenes/persona/skills) runs at the nightly review (default 22:00), ~60s after startup, or via manual /memory evolve. - /memory commands are zero-LLM: they query the local memory store directly; the command declares input, so parameterized input is handled by the command system (trigger via the command menu, /). - The memory browser (Settings → "Self-evolving memory" → "Memory" tab) lets you view/filter/correct/forget memories, the persona, scenes and synthesized skills. ## Compliance - The plugin's architecture is inspired by TencentDB Agent Memory (MIT); it is an independent implementation with no affiliation with Tencent. - The plugin and all its dependencies are MIT-licensed and run fully locally. ## Acknowledgements This project references the following open-source projects; many thanks to their authors and communities: - TencentDB Agent Memory (Tencent Cloud) — the four-layer memory pyramid (L0 capture → L1 extraction → L2 scene grouping → L3 persona) and memory-management ideas are the direct inspiration for this plugin's pipeline; - self-improving-agent (author pskoett) — a self-evolution skill in the OpenClaw ecosystem: distilling lessons, corrections and reusable flows from experience; this plugin's self-evolution module (memory consolidation / forgetting / correction + skill synthesis) takes design inspiration from it. ## Docs - README.md — this file (English) - README.zh.md — 中文版说明 - docs/ (install/verify checklists, testing guide, design docs, DSH research) — local only, excluded via .gitignore Unit tests: node scripts/test-storage.mjs / test-extract.mjs / test-recall.mjs / test-evolve.mjs / test-commands.mjs (all PASS). ## License MIT License — see LICENSE for the full text. Summary: - Grant: anyone may obtain a copy of the software and associated docs and use, copy, modify, merge, publish, distribute, sublicense and/or sell it; - Condition: the above copyright notice and permission notice must be included in all copies or substantial portions; - Disclaimer: the software is provided "AS IS" without warranty of any kind; in no event shall the authors or copyright holders be liable for any claim, damages or other liability. Copyright (c) 2026 mashao. package.json declares license: MIT.Not by stars — picked by hand, one at a time.
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