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dsh-auto-memory

Proactive associative memory and Astra-style cross-window context management for DeepSeek Harness.

VisionUI & ProductivityDeveloper ToolsBrowser & Web
129GitHub Stars10ForksUpdated2026-10-15

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Plugin Overview & Capabilities

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dsh-auto-memory provides an ambient associative memory engine and context continuity system for DeepSeek Harness. It automatically records conversations into tiered local Markdown files (user preferences, project notes, daily logs, and reflections), calculates activation eligibility using hybrid lexical and semantic embeddings, and injects relevant memories at fixed boundaries prior to model response generation without requiring explicit prompt instructions. Additionally, it implements Astra-style handoff ledgers, token water-level monitoring, external memory scanning, and a rich UI workbench in DSH.

Key Capabilities

  • Pre-response memory injection using tiered retrieval without relying on manual user recall prompts
  • Three-layer local markdown memory hierarchy encompassing user rules, workspace notes, and append-only daily logs
  • Multi-tier retrieval engine supporting zero-dep lexical BM25, built-in Transformers.js embeddings, or an optional Python BGE-M3 sidecar
  • Astra-style handoff ledgers and whiteboard continuity when token limits approach threshold
  • External session and memory scanning from tools such as Claude Code, Codex, and WorkBuddy
  • Full-featured browser workbench panel with calendar scheduling, audit ledger, and workspace mind maps

Useful For

  • Preserving critical technical decisions and context across long-running or multi-window coding sessions
  • Injecting cross-project user preferences and coding guidelines automatically into every conversation turn
  • Reviewing and auditing agent memory activations through structured evidence trails and scoring tabs
  • Migrating and unifying local memory traces left by various AI coding assistants into DeepSeek Harness

Who It Fits

  • DeepSeek Harness developers working on multi-day or complex software engineering projects
  • Users running local or offline models who require local-first, privacy-respecting memory persistence
  • Power users managing extensive cross-workspace contexts and workflow guidelines

Documented Limitations

  • Whiteboard content is currently injected into turn guidance but not yet indexed for memory_recall search
  • Advanced BGE-M3 semantic retrieval requires an optional Python sidecar and additional disk space
  • Built-in JS semantic tier requires native dependencies (@huggingface/transformers and onnxruntime-node)

DSH Compatibility

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Not tested yetNo runtime compatibility tests have been published yet.

Security Signals

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Dependency Counts

package.json declares 0 runtime, 0 development, 1 peer, and 1 optional dependencies.

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Dsh Bundle Declared

package.json declares DSH bundle metadata.

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License Declared

GitHub reports the repository license as BSD-3-Clause.

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Package Manifest Available

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Source Available

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Source & Registry Notes

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Source repository
Aik358/dsh-auto-memory
Registry source
GitHub · dsh-plugin topic
Registry classification
Plugin
Source checked
9478261 · 2026-10-17

This project is independently indexed from public source information. DSH Plugin is not affiliated with DeepSeek or the plugin author. Always check the author repository before installation.

Repository Activity

GitHub stars
129GitHub stars
Forks
10
Open issues
1
Last commit
2026-10-15
Last release
2026-10-14
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