Proactive associative memory for DSH: zero-prompt recall injected before the model speaks, three-layer auto-consolidation, skill crystallization, and Astra-style context management - handoff ledgers, PLAN whiteboard, water-level sensing. Local-first, model-agnostic, zero deps. 主动联想记忆+Astra 式上下文管理：自动唤回/自动沉淀/技能固化/交接账本与白板跨窗口续命/水位感知。
Install verification: Ecosystem app: not installed via dsh plugin add, so the L1-L5 plugin install-verification ladder does not apply; the security scan still runs.Install verification details →
What it doesAI
An auto-memory plugin for DeepSeek Harness with layered user/project/daily memory, retrieval, reflections, and a visual panel.
- Three-layer memory: user-level, project notes, daily logs
- Automatic injection/retrieval plus daily reflections
- Visual panel, settings page, and inherits other AI tools' memories
Capability tags are AI-inferred or rule-extracted from the README (see badge) — vocabulary-limited, not install-verified. AI = inferred; README = literal keyword from the readme.
Installation
Ecosystem apps are not installable via dsh plugin add: desktop / web shells install or deploy through their own release channel (GitHub Releases or the project site).
The level reads L5 · Ecosystem plugin / L5 · Ecosystem app per the three-way classification (the L1-L5 ladder does not rate them); the security scan still runs.
Verification & Compatibility
Grouped by plugin version: each card lists the dsh versions actually tested against that artifact version and their install verdicts (L5 wins). Untested combinations are omitted — absence means untested, never assumed compatible. L1–L3 are a plugin-level static archive (independent of the dsh version — the same verdict on every dsh row): they sit in each row's level grid next to L4/L5, marked "static", while their evidence is stored once per plugin inside that row's "checks & evidence" instead of being duplicated per version.
External credentials (plugin-level): none detected
| plugin ＼ dsh | dsh 0.1.7-rc.2 | dsh 0.1.7-rc.1 | dsh 0.1.6-alpha.2 | dsh 0.1.6-alpha.1 | dsh 0.1.5-rc.2 |
|---|---|---|---|---|---|
| 3.1.7 | · | · | · | · | · |
| 3.1.4 | · | · | · | · | · |
| 3.0.1 | · | · | · | · | · |
| 3.0.0 | · | · | · | · | · |
| 2.5.3 | · | · | · | · | · |
3.1.7npm2026-09-25
@a9i5k4/dsh-auto-memory
Ecosystem app: not installed via dsh plugin add (a desktop / web shell) — its level reads L5 · Ecosystem app.
3.1.4npm2026-09-23
@a9i5k4/dsh-auto-memory
Ecosystem app: not installed via dsh plugin add (a desktop / web shell) — its level reads L5 · Ecosystem app.
3.0.1npm2026-09-21
@a9i5k4/dsh-auto-memory
Ecosystem app: not installed via dsh plugin add (a desktop / web shell) — its level reads L5 · Ecosystem app.
3.0.0npm2026-09-20
@a9i5k4/dsh-auto-memory
Ecosystem app: not installed via dsh plugin add (a desktop / web shell) — its level reads L5 · Ecosystem app.
2.5.3npm2026-09-16
@a9i5k4/dsh-auto-memory
Ecosystem app: not installed via dsh plugin add (a desktop / web shell) — its level reads L5 · Ecosystem app.
Only the latest 3 published versions are shown; source-snapshot (commit hash) groups, unstated groups and older versions are omitted — the full archive stays in the data layer (snapshot/unstated groups appear only when a plugin has no published version).
Author badges
Embed the official badges in your README to showcase security & install-test status:
`[](https://www.dsh.so/artifact/dsh-auto-memory/)`Security Report
Automated static scan, not manual review.
Vet static analysis found no suspicious behavior — verdict is clean.
v3.1.7dsh manifest3.1.7npm2026-09-273.1.7same versionclean · npmVet is an AST static scan (npm artifact or git source).
Disclaimer: automated static analysis, not a security guarantee. Always review what you install.
Risk details
Activity
Last commit 2026-09-27 · activity: Active
• Repo created: 2026-08-14
• Stars: ★ 78 · Forks: 7
• Health: Active — committed within last 30 days
Source
Author README
View on GitHub ↗The author's original README from the repository — fetched live, unedited (the English page loads the default README).