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dsh-memory-setup

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Solve the AI goldfish brain: auditable personal memory for DeepSeek Harness - preferences, project conventions, workflows, error lessons. 解决 AI 金鱼脑的本地可审计记忆层。

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READMESource: main@1349dcc4

dsh-memory-setup

Solve the AI goldfish brain 🐠 — a local, auditable personal memory layer for DeepSeek Harness. Remembers your preferences, project conventions, workflows, and error lessons, and injects them back into every session.

解决 AI 的"金鱼脑":本地、可审计的个人记忆层——偏好、项目约定、工作方式、纠错教训,会话间自动继承。

Install

dsh plugin --profile <profile> add dsh-memory-setup

Tools

Tool What it does
memory_setup One-time onboarding: language, code style, tools, conventions, workflows
memory_status Read current memory + changelog (also auto-injected guidance at boot)
memory_update Update one memory path (e.g. preferences.codeStyle) with a changelog entry
memory_project Auto-extract project conventions from workspace files (README / package.json / configs), preview or apply
memory_lesson Record an error lesson (error → fix → evidence) so the same mistake is not repeated
memory_review v0.2 — formalize an incident into a lesson with root cause; similar lessons are auto-merged (dedupe + hit counter)
memory_export v0.2 — export the full memory + changelog to a Markdown file for review/backup
knowledge_add v0.3 — add a knowledge entry (title/content/tags/source); similar titles auto-merge
knowledge_search v0.3 — keyword retrieval (title ×3 / tags ×2 / content ×1 scoring)
knowledge_list / knowledge_remove v0.3 — browse / delete knowledge entries
memory_diff v0.4 — diff current memory against memory.json.bak, optionally written to memory-diff.md
memory_review_session v0.5 — bulk incident review: submit many failures at once, dedupe per item
memory_snapshot / memory_list_snapshots / memory_restore v0.6 — snapshot the memory (keeps N), list, and restore with auto-backup of the current state
memory_troubleshoot v0.6 — given an error, search past lessons + knowledge base for a known fix
knowledge_embed v0.5 — backfill embeddings for KB entries (needs embeddingEndpoint); enables semantic search

Storage & auditability

  • Location: <workspace>/.dsh-memory-setup/memory.json — plain JSON, easy to read/back up
  • Every mutation appends to changelog (when / what / why) — memory is auditable by design
  • Lessons carry an optional evidence field (file/command/observation) — no evidence, no lesson
  • Local-first: nothing leaves your machine

Config (optional)

Field Default Description
memoryDir .dsh-memory-setup memory dir relative to the session workspace
injectOnBoot true inject live memory into the system prompt (dynamic context, refreshed on save)
maxMemoryChars 6000 cap for rendered memory text
lessonTtlDays 90 lessons expire after this many days (0 disables)
changelogCap 100 max changelog entries kept
backupOnSave true write memory.json.bak before every save
reviewReminder true append self-review reminder to guidance
embeddingEndpoint (empty) OpenAI-compatible embeddings endpoint (enables semantic KB search)
embeddingKey (empty) Bearer key for the embeddings endpoint
embeddingModel text-embedding-3-small embeddings model name
snapshotKeep 10 max memory snapshots kept
troubleshootReminder true append troubleshoot/snapshot reminder to guidance

Roadmap

  • v0.2 ✅: incident review with dedupe (memory_review), lesson/convention expiry + changelog cap (auto-pruned on save), memory.json.bak backup on every save, Markdown export (memory_export)
  • v0.3 ✅: personal knowledge base (knowledge_*, keyword retrieval, title-merge dedupe); dynamic memory injection via a live systemPrompt.context() section — refreshed at boot (from the workspace path) and after every memory save (throttled 30s), with static guidance as fallback
  • v0.4 ✅: BM25 retrieval for the knowledge base (title ×3 / tags ×2 / content ×1, IDF-scaled — no embeddings, no deps), memory diff export (memory_diff vs backup), self-review reminder in the injected guidance
  • v0.5 ✅: optional embeddings provider (OpenAI-compatible endpoint; knowledge_embed backfill + cosine retrieval, BM25 fallback), bulk incident review (memory_review_session), own-tool fs failure tracking surfaced into the injected context
  • v0.6 ✅: memory snapshots & restore (memory_snapshot / memory_list_snapshots / memory_restore, capped, index-file based), fault troubleshooting (memory_troubleshoot — lessons + knowledge lookup), troubleshoot reminder in guidance
  • v0.7: lesson auto-detection (pending a tool-call event API), KB snapshots, memory stats page

Security

Memory plugins are the highest-trust plugin type — see SECURITY.md for the audit posture.

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