agent-memory
A hybrid memory system that provides persistent, searchable knowledge management for AI agents.
Install
npx skills add https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/agent-memory
claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install sickn33-agentic-awesome-skills@llmmart
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
agentMemoryis already installed in the project:ls -la .agentMemory
Setup
Install Dependencies:
npm installBuild the Project:
npm run compileStart 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
- Initialization: The first time you run this in a project, it may attempt to import existing markdown memory banks from
.kilocode/,.clinerules/, or.roo/. - Development Loop:
- Before Task: Search memory for relevant context.
- During Task: Use read/search to answer questions.
- After Task: Write new findings to memory.
- 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.
Comments (0)
Sign in to join the conversation.
Reviews (0)
No reviews yet.
No comments yet.