/agent-memory
A hybrid memory system that provides persistent, searchable knowledge management for AI agents.
$ npx -y skills add sickn33/antigravity-awesome-skills --skill agent-memory --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/agent-memory
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A hybrid memory system that provides persistent, searchable knowledge management for AI agents.
SKILL.md
agent-memory.SKILL.mdname: 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:
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.
Read more
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:
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.
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