Memory-as-a-Service for AI agents. Store and recall memories with semantic vector search. 100 free calls per wallet, then x402 micropayments. Your wallet add...
数据来源:ClawHub。 在 ClawSkills 查看
选择你使用的 Agent
方法一:命令行安装(推荐)
推荐(无需提前安装 clawhub)
npx clawhub@latest --dir ~/.claude/skills install memoclaw或使用 clawhub CLI(需提前安装)
clawhub --dir ~/.claude/skills install memoclaw⚠️ 需要 Node.js 18+,没有 Node?请使用下方方法二直接下载 ZIP。 安装 Node.js →
方法二:手动下载安装(无需 Node)
下载 ZIP,解压后将文件夹放到以下路径,重启 Agent 即可:
安装路径
~/.claude/skills/memoclaw/💡解压后将文件夹放到上方路径,重启 Agent 即可生效
--- name: memoclaw version: 1.23.5 description: | Memory-as-a-Service for AI agents. Store and recall memories with semantic vector search. 100 free calls per wallet, then x402 micropayments. Your wallet address is your identity. allowed-tools: - exec ---
Persistent memory for AI agents. Store text, recall it later with semantic search.
No API keys. No registration. Your wallet address is your identity.
Every wallet gets 100 free API calls — just sign and go. After that, embedding-backed calls split into two x402 tiers: store/update/recall/batch update stay at $0.005, while context/extract/ingest/consolidate/migrate cost $0.01 (all paid in USDC on Base).
---
Before using any MemoClaw command, ensure setup is complete:
which memoclaw — if missing: npm install -g memoclawmemoclaw config check — if not: memoclaw initmemoclaw status — if 0: fund wallet with USDC on BaseIf memoclaw init has never been run, all commands will fail. Run it first — it's interactive and takes 30 seconds.
---
> 📖 For full end-to-end examples (session flows, migration, multi-agent patterns, cost breakdown), see examples.md.
Essential commands:
memoclaw store "fact" --importance 0.8 --tags t1,t2 --memory-type preference # save ($0.005) [types: correction|preference|decision|project|observation|general]
memoclaw store --file notes.txt --importance 0.7 --memory-type general # store from file ($0.005)
echo -e "fact1\nfact2" | memoclaw store --batch --memory-type general # batch from stdin ($0.04)
memoclaw store "fact" --pinned --immutable --memory-type correction # pinned + locked forever
memoclaw recall "query" # semantic search ($0.005)
memoclaw recall "query" --min-similarity 0.7 --limit 3 # stricter match
memoclaw search "keyword" # text search (free)
memoclaw context "what I need" --limit 10 # LLM-ready block ($0.01)
memoclaw core --limit 5 # high-importance foundational memories (free)
memoclaw list --sort-by importance --limit 5 # top memories (free)
memoclaw whoami # print your wallet address (free)
Management commands:
memoclaw update <uuid> --content "new text" --importance 0.9 # update in-place ($0.005 if content changes)
memoclaw edit <uuid> # open memory in $EDITOR for interactive editing (free)
memoclaw pin <uuid> # pin a memory (exempt from decay) (free)
memoclaw unpin <uuid> # unpin a memory (free)
memoclaw lock <uuid> # make memory immutable (free)
memoclaw unlock <uuid> # make memory mutable again (free)
memoclaw copy <uuid> # duplicate a memory with a new ID (free)
memoclaw copy <uuid> --namespace other-project # duplicate into a different namespace
memoclaw move <uuid> --namespace archive # move memory to another namespace (free)
memoclaw move <uuid1> <uuid2> --namespace archive # move multiple memories at once
memoclaw move --from-namespace staging --namespace production # move all from one namespace to another
memoclaw move --tags stale --namespace archive # move by tag filter
memoclaw move --from-namespace old --since 30d --namespace recent # move with date filter
memoclaw move --from-namespace staging --namespace prod --dry-run # preview without moving
memoclaw move --from-namespace old --namespace archive --yes # skip confirmation prompts
memoclaw tags # list all unique tags across memories (free)
memoclaw tags --namespace project-alpha # list tags in a specific namespace
memoclaw watch # stream new memories in real-time (polls API)
memoclaw watch --namespace myproject --json # watch filtered, JSON output for piping
memoclaw ingest --text "raw text to extract facts from" # auto-extract + dedup ($0.01)
memoclaw ingest --text "raw text" --auto-relate # extract + auto-link related facts ($0.01)
memoclaw extract "fact1. fact2. fact3." # split into separate memories ($0.01)
memoclaw consolidate --namespace default --dry-run # merge similar memories ($0.01)
memoclaw suggested --category stale --limit 10 # proactive suggestions (free)
memoclaw migrate ./memory/ # import .md files ($0.01)
memoclaw diff <uuid> # show content changes between versions (free)
memoclaw diff <uuid> --all # show all diffs in sequence (free)
memoclaw upgrade # check for and install CLI updates
memoclaw upgrade --check # check only, don't install
memoclaw alias set myname <uuid> # local shortcut for a memory ID (free)
memoclaw snapshot create --name before-purge # local backup before destructive ops (free)
Importance cheat sheet: 0.9+ corrections/critical · 0.7–0.8 preferences · 0.5–0.6 context · ≤0.4 ephemeral
Memory types: correction (180d) · preference (180d) · decision (90d) · project (30d) · observation (14d) · general (60d)
Free commands: list, get, delete, bulk-delete, purge, search, core, suggested, relations, history, diff, export, import, namespace list, stats, count, browse, config, graph, completions, whoami, status, upgrade, pin, unpin, lock, unlock, edit, copy, move, tags, watch, alias, snapshot create/list/delete
---
Use this to decide whether MemoClaw is the right tool for a given situation:
Is the information worth remembering across sessions?
├─ NO → Don't store. Use context window or local scratch files.
└─ YES → Is it a secret (password, API key, token)?
├─ YES → NEVER store in MemoClaw. Use a secrets manager.
└─ NO → Is it already stored?
├─ UNKNOWN → Recall first (or `search` for free keyword lookup), then decide.
├─ YES → Is the existing memory outdated?
│ ├─ YES → Update the existing memory (PATCH).
│ └─ NO → Skip. Don't duplicate.
└─ NO → How much information?
├─ Single fact → Store it.
│ ├─ User preference/correction → importance 0.8-0.95
│ ├─ Decision or architecture → importance 0.85-0.95
│ ├─ Factual context → importance 0.5-0.8
│ └─ Ephemeral observation → importance 0.3-0.5 (or skip)
└─ Multiple facts / raw conversation → Use `ingest` (auto-extract + dedup)
Need to retrieve memories?
├─ Need high-importance foundational facts (session start)? → memoclaw core (FREE)
├─ Know the exact keyword or phrase? → memoclaw search "keyword" (FREE)
├─ Need semantic similarity match? → memoclaw recall "query" ($0.005)
└─ Need an LLM-ready context block for a prompt? → memoclaw context "query" ($0.01)
...
安装 Memoclaw Skill 后,可以对 AI 说这些话来触发它
Help me get started with Memoclaw Skill
Explains what Memoclaw Skill does, walks through the setup, and runs a quick demo based on your current project
Use Memoclaw Skill to memory-as-a-Service for AI agents
Invokes Memoclaw Skill with the right parameters and returns the result directly in the conversation
What can I do with Memoclaw Skill in my marketing & growth workflow?
Lists the top use cases for Memoclaw Skill, with example commands for each scenario
将技能文件夹放到 ~/.claude/skills/memoclaw/ 目录(个人级,所有项目可用),或 .claude/skills/memoclaw/(项目级)。重启 AI 客户端后,用 /memoclaw 主动调用,或让 AI 根据上下文自动发现并使用。
Memoclaw Skill 支持 Claude、Cursor、OpenClaw,可与这些 AI 平台无缝集成,扩展其能力。
Memoclaw Skill 可免费安装使用。请查阅仓库了解许可证信息。
Memory-as-a-Service for AI agents. Store and recall memories with semantic vector search. 100 free calls per wallet, then x402 micropayments. Your wallet add...
Memoclaw Skill 属于「Marketing & Growth」分类,该分类的技能帮助 AI 智能体在此领域执行专业任务。
Automate my marketing & growth tasks using Memoclaw Skill
Identifies repetitive steps in your workflow and sets up Memoclaw Skill to handle them automatically