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

▼
bash
复制代码
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 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 ✅: 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.

dsh-memory-setup

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。

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 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

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

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 ✅: 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