Memory Skill — Development skill for Claude Code

Memory Skill

A file-based long-term memory skill for AI agents, implemented using a single append-only JSONL file. This skill allows agents to persist information across sessions and retrieve it efficiently using standard Unix tools.

Features

• File-based Storage: Uses a simple JSONL (JSON Lines) file for storage, making it easy to inspect and backup.
• Append-Only: Ensures data integrity by only appending new entries and never rewriting existing lines.
• Efficient Search: Prioritizes recent entries by searching from the end of the file using a configurable window.
• Lightweight: Depends only on standard Unix tools like bash, jq, and ripgrep (or grep).

Usage

This skill provides two main capabilities to the agent:

1. Writing to Memory (`memory_write`)

Stores a new entry in the memory file. Each entry is a JSON object containing a timestamp, type, content, and optional tags/metadata.

**Input:**

• type: String (e.g., "note", "fact", "task", "todo")
• content: String (the raw text content)
• tags: (Optional) Array of strings
• meta: (Optional) JSON object for extra metadata

**Storage Format:** Entries are stored in `~/.codex/memory.jsonl` (default) as:

{"ts": "2023-10-27T10:00:00+00:00", "type": "note", "content": "User prefers Python.", "tags": ["preference"], "meta": null}

2. Searching Memory (`memory_search`)

Retrieves relevant entries from memory based on a query string.

**Input:**

• q: Query string (literal substring or regex)
• limit: (Optional) Max number of results to return (default: 20)
• window_lines: (Optional) Number of recent lines to search (default: 50000)

The search strategy uses a "hybrid" approach:

1. Reads the last window_lines of the file.
2. Filters lines using rg (ripgrep) or grep.
3. Parses valid JSON lines with jq.
4. Returns the most recent matches.

Requirements

Ensure the environment has the following tools installed:

• bash
• jq
• ripgrep (recomm