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Skill · AI Ml

Agent memory

A hybrid memory system that provides persistent, searchable knowledge management for AI agents.

Agentic Awesome SkillsLicense: MITAdded Sep 5, 2026
Use it in my AI

How to use it

  1. Start your plan and connect your AI once
  2. Add the skill to your AI, one time only: press Copy skill and paste it into your AI's instructions: a project in ChatGPT, Claude or Grok, a Gem in Gemini, an agent in Microsoft 365 Copilot, or a rule in Cursor. It stays there for every new chat. In Kimi, paste it at the start of a new chat.
  3. Ask for the task in your own words, or say it directly:
Use the Agent memory skill to help me with this.
SKILL.md

agentMemory Skill

When to Use

Use this skill when you need a hybrid memory system that provides persistent, searchable knowledge management for AI agents.

This skill extends your capabilities by providing a persistent, searchable memory bank that automatically syncs with project documentation.

Prerequisites

  • Node.js installed
  • Check if agentMemory is already installed in the project:
  • ``bash ls -la .agentMemory ``

Setup

  1. Install Dependencies:
  2. ``bash npm install ``

  1. Build the Project:
  2. ``bash npm run compile ``

  1. Start the Memory Server:
  2. You need to run the MCP server to interact with the memory bank. ``bash npm run start-server <project_id> <absolute_path_to_workspace> `` Note: This skill typically runs as a background process or via an mcp-server configuration. ensuring it is running is key.

Capabilities (MCP Tools)

Once the server is running, you can use these tools:

memory_search

Search for memories by query, type, or tags.

  • Args: query (string), type? (string), tags? (string[])
  • Usage: "Find all authentication patterns" -> memory_search({ query: "authentication", type: "pattern" })

memory_write

Record new knowledge or decisions.

  • Args: key (string), type (string), content (string), tags? (string[])
  • Usage: "Save this architecture decision" -> memory_write({ key: "auth-v1", type: "decision", content: "..." })

memory_read

Retrieve specific memory content by key.

  • Args: key (string)
  • Usage: "Get the auth design" -> memory_read({ key: "auth-v1" })

memory_stats

View analytics on memory usage.

  • Usage: "Show memory statistics" -> memory_stats({})

Workflow

  1. Initialization: The first time you run this in a project, it may attempt to import existing markdown memory banks from .kilocode/, .clinerules/, or .roo/.
  2. Development Loop:
  • Before Task: Search memory for relevant context.
  • During Task: Use read/search to answer questions.
  • After Task: Write new findings to memory.
  1. Sync: Your writes are automatically synced to standard markdown files in the project.

Example

User request:

Use @agent-memory for this task: A hybrid memory system that provides persistent, searchable knowledge management for AI agents.

Limitations

  • Use this skill only when the task clearly matches its upstream source and local project context.
  • Verify commands, generated code, dependencies, credentials, and external service behavior before applying changes.
  • Do not treat examples as a substitute for environment-specific tests, security review, or user approval for destructive or costly actions.