Does it save every error I encounter during a session?

No, the skill is designed to ignore issue-specific errors and only store general knowledge that remains helpful for different tasks in the future.

Does the agent save data to my repository automatically?

No, the agent will always list the specific items it plans to save and ask for your explicit confirmation before updating the AGENTS.md file.

What is the purpose of the agent-memory skill?

It allows Claude to save and retrieve specific knowledge about a repository, such as build commands, project structure, and style guides, using a persistent AGENTS.md file.

How do I trigger a memory update?

You can use the /remember command to prompt the agent to summarize its recent observations and suggest valuable information to be saved for future use.

Where is the memory data stored?

The data is stored in a file named AGENTS.md (or repo.md) located at the root of your repository, making the knowledge specific to that project.

Agent Memory

Name: Agent Memory
Author: OpenHands

byOpenHands

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Productivity & Workflow

Persists and retrieves repository-specific knowledge to maintain context across different AI coding sessions.

About

Agent Memory provides a standardized way for Claude to retain crucial details about a codebase by utilizing AGENTS.md files at the repository root. It automatically captures and stores repository structures, build commands, code styles, and custom workflows, ensuring that every future interaction starts with a deep understanding of your project's unique requirements. By acting as a persistent long-term memory, it eliminates the need to re-explain project basics, setup procedures, and development standards every time a new session begins.

Key Features

User-controlled knowledge updates with explicit confirmation prompts
Persistent storage of build, lint, and test commands
Automated repository structure mapping and documentation
Intelligent filtering to exclude temporary issue-specific data
40 GitHub stars
Automatic context injection from existing AGENTS.md files

Use Cases

Maintaining a persistent source of truth for repository commands to prevent AI hallucinations
Onboarding an AI agent to a complex codebase with non-standard build scripts
Standardizing code style and workflow preferences for AI-assisted development

About

Key Features

User-controlled knowledge updates with explicit confirmation prompts
Persistent storage of build, lint, and test commands
Automated repository structure mapping and documentation
Intelligent filtering to exclude temporary issue-specific data
40 GitHub stars
Automatic context injection from existing AGENTS.md files

Use Cases

Maintaining a persistent source of truth for repository commands to prevent AI hallucinations
Onboarding an AI agent to a complex codebase with non-standard build scripts
Standardizing code style and workflow preferences for AI-assisted development