Agent skill

memory-store

Store a memory in ourmem. Use when user says remember, save, store, or don't forget something.

Stars 186
Forks 4

Install this agent skill to your Project

npx add-skill https://github.com/ourmem/omem/tree/main/plugins/claude-code/skills/memory-store

SKILL.md

Memory Store

Save information to ourmem for persistent memory across sessions.

How to store

bash
curl -sf \
  -X POST \
  -H "X-API-Key: $OMEM_API_KEY" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  "${OMEM_API_URL:-https://api.ourmem.ai}/v1/memories" \
  -d '{"content": "$ARGUMENTS", "tags": ["manual"], "source": "claude-code"}'

Replace $ARGUMENTS with the content to store.

Response Format

The API returns the created memory:

json
{
  "id": "...",
  "content": "...",
  "tags": ["manual"],
  "source": "claude-code",
  "created_at": "..."
}

Expand your agent's capabilities with these related and highly-rated skills.

ourmem/omem

ourmem

Shared memory that never forgets. Cloud hosted or self-deployed. Collective intelligence for AI agents with Space-based sharing across agents and teams. Use when users say: - "install ourmem" / "install omem" - "setup memory" / "setup omem" - "add memory plugin" - "ourmem onboarding" / "omem onboarding" - "memory not working" - "remember this" - "save this for later" - "don't forget" - "recall preferences" - "what did I say last time" - "import memories" - "share memories" - "share with user" - "share memories to someone" - "team memory" - "shared space" - "persistent memory" - "cross-session memory" - "collective intelligence" - "memory analytics" - "memory stats" - "self-host memory" - "deploy memory server" Even if the user doesn't say "ourmem" or "omem", trigger when they want persistent memory, memory sharing between agents, memory analytics, or memory import/export.

186 4
Explore
ourmem/omem

memory-recall

Search and recall memories from ourmem. Use when user asks to find, recall, search, or remember something.

186 4
Explore
davila7/claude-code-templates

verl-rl-training

Provides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.

23,776 2,298
Explore
davila7/claude-code-templates

openrlhf-training

High-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2× faster than DeepSpeedChat with distributed architecture and GPU resource sharing.

23,776 2,298
Explore
davila7/claude-code-templates

gguf-quantization

GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.

23,776 2,298
Explore
davila7/claude-code-templates

Claude Code Guide

Master guide for using Claude Code effectively. Includes configuration templates, prompting strategies "Thinking" keywords, debugging techniques, and best practices for interacting with the agent.

23,776 2,298
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results