Agent memory

Skill sickn33/agentic-awesome-skills/skills/agent-memory

AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 1,987+ agentic skills. Includes CLI, local MCP, catalog, plugins, and Workbench.

Install

npx -y skills add sickn33/agentic-awesome-skills --skill agent-memory

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What its author says it does

Copied from the file, not written here

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

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

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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

Install Dependencies:
```
npm install
```
Build the Project:
```
npm run compile
```
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

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.