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agent-memory

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

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Download sickn33-agentic-awesome-skills-skills_agent-memory-286166a.zip · 1 KB
Part of sickn33/agentic-awesome-skills — 427 skills
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Install

skills CLI npx skills add https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/agent-memory
Claude Code claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install sickn33-agentic-awesome-skills@llmmart
Git git clone https://github.com/sickn33/agentic-awesome-skills.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole sickn33/agentic-awesome-skills collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

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:
    ls -la .agentMemory
    

Setup

  1. Install Dependencies:

    npm install
    
  2. Build the Project:

    npm run compile
    
  3. Start the Memory Server: You need to run the MCP server to interact with the memory bank.

    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.
  3. Sync: Your writes are automatically synced to standard markdown files in the project.

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.
Files (agentic-awesome-skills)
  • SKILL.md 2.9 KB
    ---
    name: agent-memory
    description: A hybrid memory system that provides persistent, searchable knowledge management for AI agents.
    risk: critical
    source: https://github.com/webzler/agentMemory/tree/main/
    source_repo: webzler/agentMemory
    source_type: community
    date_added: 2026-07-01
    license: MIT
    license_source: https://github.com/webzler/agentMemory/blob/main/LICENSE
    ---
    
    # 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**:
       ```bash
       npm install
       ```
    
    2. **Build the Project**:
       ```bash
       npm run compile
       ```
    
    3. **Start the Memory Server**:
       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.
    3. **Sync**: Your writes are automatically synced to standard markdown files in the project.
    
    ## 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.
    

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