Agentic Loop Memory Server Skill ♾️

This skill connects you to the @mhrj/mcp-agent-loop server. This server provides you with persistent memory, preventing you from forgetting your overarching goal or crashing due to context window limits when working on complex, multi-step tasks.

How it Works

When you are asked to perform a complex, autonomous, or long-running task, you must rely on this MCP server instead of trying to hold the entire history in your immediate memory window.

1. Start the Session Run the init_loop tool with a unique session_id (e.g. debug_auth_bug) and the objective.

2. Read the State Read the MCP resource loop://{session_id}. This Markdown file is your "brain". It contains the Objective, your System Instructions, the Active Context (recent steps), and your Compacted History (what you completed hours/days ago).

3. Act and Log Perform your normal tasks (running bash commands, editing files, searching). After every significant action, you MUST call the log_step tool:

• session_id: Your chosen ID.

• action: What you tried to do.

• result: The command output or file edit result.

• failed: A boolean. true if the command threw an error or didn't do what you expected. false if it succeeded.

4. The Self-Healing Requirement (CRITICAL) If you set failed: true in log_step, you MUST provide a self_heal_strategy. This is because you are not allowed to mindlessly retry the same failing tool. If a grep search fails to find a variable, your self_heal_strategy might be: "The variable isn't in src. I will search in the lib directory or look for tool suggestions." If you forget the self_heal_strategy, the log_step tool will explicitly reject your call and make you try again.

5. The Compaction Requirement (CRITICAL) If you run for a long time, the Active Context in your state file will grow too large, causing you to crash or hallucinate. When log_step returns a warning that the context is too large (e.g., >3000 words), you MUST immediately stop working on the task and call the compact_memory tool.

• context_summary: You must look at the Active Context and write a dense, 2-3 paragraph summary of what was achieved and what the current state is. The server will wipe the Active Context and permanently store your summary.

6. Asking the Human If you hit an absolute dead end (e.g., missing API keys, ambiguous requirements, infinite error loops), do NOT guess. Call the report_blocker tool. Doing this will pause the loop, allowing you to ask the human user for help via standard chat. Once the human replies, use the resume_loop tool to inject their input back into the state file.

Expected Behavior

You are expected to act like a senior engineer. Do not give up easily. If an action fails, use your reasoning to devise a new self_heal_strategy. If you exhaust all local tools, call get_tool_suggestions to remind yourself how to break out of the box.