dsh-memory-setup
by 863683348
解决 AI 金鱼脑:本地可审计的个人记忆层——偏好、项目约定、工作流与纠错教训,以带变更日志与完整性校验的 JSON 持久化在工作区,支持一次性设置、项目约定自动提取、证据化教训与快照恢复。
Local, auditable personal memory for DeepSeek Harness: preferences, project conventions, workflows and error lessons persisted as a changelogged JSON file in the workspace, with onboarding, auto project-convention extraction and evidence-backed lessons.
安装
dsh plugin --profile web add github:863683348/dsh-memory-setupGitHub 源码安装:首次需按提示配置 allowBuilds 构建授权后重试
安装与环境配置指引、插件开发教程见 DSH 中文社区文档 ↗
安装即在你的机器上以你的权限运行第三方代码——它可读写文件、使用凭据、访问网络,DSH 的工具审批不会为插件代码加沙箱。「检测到 manifest」仅代表发现 dsh.bundle / dsh.plugin 清单,不构成兼容性或安全审查;安装前请审阅源码,不熟悉的插件先在不含密钥的环境试用。
README
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.
原始 README: https://github.com/863683348/dsh-memory-setup/blob/main/README.md ↗
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