
pin
Pins or unpins a memory to protect it from pruning during dream consolidation. Use when a memory is critical and must never be removed, such as architecture decisions, security constraints, or immutable team conventions.
- Installs
- 93
- Last 24h
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- Trending rank
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- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/mem0ai/mem0 --skill pin- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads pin automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Mem0 Pin
Pin a memory to mark it as high-priority and protect from pruning.
Execution
Step 1: Find the memory
The user provides either a search query or memory ID.
If memory ID:
- Call
get_memorywith the ID.
If search query:
- Call
search_memorieswith the query,filters={"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}]},top_k=5. - Show numbered list with content previews.
- Ask: "Which memory to pin? Enter a number."
Step 2: Read current content
Call get_memory with the selected memory ID. Store:
original_text— the memory's text contentoriginal_metadata— the existingmetadatadict
Step 3: Pin it
The MCP update_memory tool only accepts memory_id, text, and source — it
does not accept a metadata parameter. To pin, append a pin marker to the text:
pinned_text = "[PINNED] " + original_text if not original_text.startswith("[PINNED]") else original_text
update_memory(memory_id=<selected_id>, text=pinned_text)
For new memories (user wants to pin text that isn't stored yet):
- Call
add_memorywith:text="[PINNED] <the user's text>"user_id=<active_user_id>app_id=<active_project_id>metadata={"pinned": true, "type": "decision", "confidence": 1.0}infer=False
- The response contains
event_id. Callget_event_status(event_id=<event_id>)once to retrieve the memory ID, then confirm.
Step 4: Confirm
Pinned: "<memory content, first 80 chars>"
Memory ID: <id>
Append ... only if content exceeds 80 characters.
Unpin
If the user says "unpin":
- Call
get_memoryto read current content. - Remove the pin marker from the text:
unpinned_text = original_text.removeprefix("[PINNED] ") update_memory(memory_id=<id>, text=unpinned_text) - Print:
Unpinned: "<content>..."
FAQ
What does the pin skill do?
Pins or unpins a memory to protect it from pruning during dream consolidation. Use when a memory is critical and must never be removed, such as architecture decisions, security constraints, or immutable team conventions.
How do I install pin?
Run npx skills add https://github.com/mem0ai/mem0 --skill pin in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/pin/ (personal) or .claude/skills/pin/ (project).
Which AI agents can use pin?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is pin safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains pin?
It is published by mem0ai in mem0ai/mem0. It has 93 recorded installs.
More from mem0ai/mem0
mem0
mem0ai/mem0
Mem0 Platform SDK for adding persistent memory to AI applications. TRIGGER when: user mentions "mem0", "MemoryClient", "memory layer", "remember user preferences", "persistent context", "personalization", or needs to add long-term memory to chatbots, agents, or AI apps. Covers Python SDK (mem0ai), TypeScript SDK (mem0ai), and framework integrations (LangChain, CrewAI, OpenAI Agents SDK, Pipecat, LlamaIndex, AutoGen, LangGraph). Also covers the open-source self-hosted Memory class. This is the DEFAULT mem0 skill for ambiguous queries. DO NOT TRIGGER when: user asks about CLI commands, terminal usage, or shell scripts (use mem0-cli), or Vercel AI SDK / @mem0/vercel-ai-provider / createMem0 (use mem0-vercel-ai-sdk).
mem0-cli
mem0ai/mem0
Mem0 CLI -- the command-line interface for mem0 memory operations. TRIGGER when: user mentions "mem0 cli", "mem0 command line", "@mem0/cli", "mem0-cli", "pip install mem0-cli", "npm install -g @mem0/cli", or is running mem0 commands in a terminal/shell (mem0 add, mem0 search, mem0 list, mem0 get, mem0 init, mem0 config, mem0 import). Also triggers when query includes CLI flags like --user-id, --output, --json, --agent, or describes bash/zsh/terminal/shell usage. DO NOT TRIGGER when: user asks about programmatic SDK integration in Python/TS code (use mem0 skill), or Vercel AI SDK provider (use mem0-vercel-ai-sdk skill).
mem0-vercel-ai-sdk
mem0ai/mem0
Mem0 provider for Vercel AI SDK (@mem0/vercel-ai-provider). TRIGGER when: user mentions "vercel ai sdk", "@mem0/vercel-ai-provider", "createMem0", "retrieveMemories", "addMemories", "getMemories", "searchMemories", "mem0 vercel", "AI SDK provider", "AI SDK memory", or is using generateText/streamText with mem0. Also triggers for Next.js apps needing memory-augmented AI. DO NOT TRIGGER when: user asks about direct Python/TS SDK calls without Vercel (use mem0 skill), or CLI terminal commands (use mem0-cli skill).
mem0-test-integration
mem0ai/mem0
Open the skill to read its SKILL.md instructions.
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