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dsh-memory-setup
863683348/dsh-memory-setup
Mémoire personnelle locale et auditable pour DeepSeek Harness : préférences, conventions de projet, flux de travail et leçons d'erreurs persistés dans un fichier JSON avec journal des modifications dans l'espace de travail, avec onboarding, extraction automatique des conventions de projet et leçons appuyées par des preuves.
Installer
dsh plugin --profile web add github:863683348/dsh-memory-setupREADME
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 |
memory_stats | v0.7 — aggregate stats across memory, knowledge base and snapshots |
memory_promote | v0.7 — promote recurring lessons (hits ≥ threshold) into standing conventions; auto-runs on save |
memory_import / memory_merge | v0.8 — import memory from JSON (auto-migrate) / merge two memories (newer or both) |
kb_export / kb_import | v0.8 — knowledge base JSON round-trip |
memory_focus | v0.9 — relevance-based injection: only memory matching a topic is injected |
memory_tier | v1.0 — hot/warm/cold tiers (hot is injected, cold is archived) |
memory_audit | v1.0 — sha256 integrity check + changelog audit report |
memory_import_claude | v1.1 — import conventions from CLAUDE.md |
memory_export_all / memory_import_all | v1.2 — full backup bundle (memory + KB + snapshots) |
memory_annotate | v1.2 — owner/purpose annotations on entries |
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
evidencefield (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.bakbackup on every save, Markdown export (memory_export) - v0.3 ✅: personal knowledge base (
knowledge_*, keyword retrieval, title-merge dedupe); dynamic memory injection via a livesystemPrompt.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_diffvs backup), self-review reminder in the injected guidance - v0.5 ✅: optional embeddings provider (OpenAI-compatible endpoint;
knowledge_embedbackfill + 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 ✅: KB included in snapshots (snapshot/restore both memory + knowledge), lesson auto-promotion (recurring lessons with hits ≥ threshold become standing conventions, auto-run on save — the memory literally learns from repeated mistakes), memory stats (
memory_stats) - v0.8 ✅: schema v2 migration (auto on load), memory import/merge (
memory_import/memory_merge, newer/both conflicts), knowledge base JSON round-trip (kb_export/kb_import) - v0.9 ✅: lesson health evaluation (failing/resolved/active — auto on save, ⚠️ markers in render), relevance-focused injection (
memory_focus) - v1.0 ✅: tiers (hot/warm/cold), integrity audit (
memory_audit, sha256), privacy redaction in exports (sensitiveKeys) - v1.1 ✅: optimistic locking (revision-based CAS — multi-session/multi-agent safe), CLAUDE.md import (
memory_import_claude) - v1.2 ✅: full backup bundle (
memory_export_all/memory_import_all— memory + KB + snapshots), annotations (memory_annotate, owner/purpose) — team-ready - v1.3+: lesson auto-detection (pending a tool-call event API), web stats view
Security
Memory plugins are the highest-trust plugin type — see SECURITY.md for the audit posture.