AGENT SKILL

mem0-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.

License 许可
Apache-2.0
最近更新
2026-08-12
Stars
★ 2
Forks
0

01 前言 Front Matter

name
mem0-pin
description
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.

03 SKILL.md 正文

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_memory with the ID.

If search query:

  • Call search_memories with 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 content
  • original_metadata — the existing metadata dict

Step 3: Pin it

The update_memory tool updates a memory by id. To pin durably, append a pin marker to the text so it travels with the memory:

pinned_text = "[PINNED] " + original_text if not original_text.startswith("[PINNED]") else original_text
update_memory(id=<selected_id>, text=pinned_text)

For new memories (user wants to pin text that isn't stored yet):

  1. Call add_memory with:
    • 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
  2. The response contains event_id. Call get_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":

  1. Call get_memory to read current content.
  2. Remove the pin marker from the text:
    unpinned_text = original_text.removeprefix("[PINNED] ")
    update_memory(memory_id=<id>, text=unpinned_text)
    
  3. Print: Unpinned: "<content>..."

Output formatting

IMPORTANT: Do NOT use markdown in your output. OpenCode TUI renders text verbatim — markdown like bold, ## headers, and | table | syntax appears as raw characters. Use plain text with indentation for structure. Use dashes for lists. Use spaces to align columns instead of markdown tables.

04 同仓库更多 Skills

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zhangmask/C_AnimeCompanion

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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).

★ 2
zhangmask
zhangmask/C_AnimeCompanion

mem0-vercel-ai-sdk

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).

★ 2
zhangmask
zhangmask/C_AnimeCompanion

mem0-test-integration

Verify a Mem0 integration produced by /mem0-integrate. Runs in the same workspace on the same branch (loose coupling) — installs dependencies, runs the repo's native test suite, then exercises a real end-to-end smoke flow against the user's API key. Produces a scorecard. TRIGGER when: user has just run /mem0-integrate and says "verify", "test the integration", "run /mem0-test-integration", or when a .mem0-integration/ directory exists and tests have not been run yet on the current branch. DO NOT TRIGGER when: the user wants to run general project tests (defer to the repo's native test command), or when no prior /mem0-integrate run exists in the current branch (ask them to run /mem0-integrate first). This skill ONLY catches compile and runtime bugs by design. Logical integration errors — wrong data stored, wrong time retrieved, wrong user scoping — are on the human reviewer.

★ 2
zhangmask
zhangmask/C_AnimeCompanion

mem0-oss-to-platform

Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local `Memory` class) to the mem0 Platform / hosted / managed SDK (the `MemoryClient` class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g. "migrate my mem0 setup to the platform", "switch from self-hosted mem0 to MemoryClient", "use my mem0 API key instead of a local Qdrant", "move mem0 to the cloud/hosted/managed service", or "replace my local mem0 vector store + embedder config with the platform". Applies to Python (`from mem0 import Memory` → `from mem0 import MemoryClient`) and TypeScript/JavaScript (`import { Memory } from "mem0ai/oss"` → `import MemoryClient from "mem0ai"`). Trigger even when the user doesn't say the word "migrate" but clearly wants their existing mem0 integration to run against the hosted platform. It first produces a reviewable migration plan, then executes it after the developer approves. Strictly scoped to the mem0 integration — it does not refactor, restructure, or "improve" any unrelated code.

★ 2
zhangmask
zhangmask/C_AnimeCompanion

mem0-integrate

Integrate Mem0 into an existing repository using a goal-driven, TDD pipeline. Detects the repo's language automatically and asks the user to pick between Mem0 Platform (managed) and Mem0 Open Source (self-hosted). Writes failing tests before any implementation. Produces a local feature branch plus `.mem0-integration/` artifacts consumed by the paired verification skill. TRIGGER when: user says "integrate mem0", "add mem0 to this repo", "wire mem0 into <repo>", or asks how to add memory to an existing project. DO NOT TRIGGER when: the user wants general SDK usage (use skill:mem0), CLI usage (use skill:mem0-cli), or Vercel AI SDK (use skill:mem0-vercel-ai-sdk). After success, invoke skill:mem0-test-integration to verify in the same workspace (loose coupling).

★ 2
zhangmask
zhangmask/C_AnimeCompanion

mem0-cli

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).

★ 2