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.