learning-loop

Dependencies

This skill requires Python 3.8+ and standard library only. No external packages needed.

To install this skill's dependencies:

pip-compile ./requirements.in
pip install -r ./requirements.txt

See ./requirements.txt for the dependency lockfile (currently empty — standard library only).

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Learning Loop

The Learning Loop is a structured cognitive continuity protocol ensuring that knowledge survives across isolated agent sessions. It is designed to be universally applicable to any agent framework.

CRITICAL: Anti-Simulation Rules

YOU MUST ACTUALLY PERFORM THE STEPS LISTED BELOW. Describing what you "would do", summarizing expected output, or marking a step complete without actually doing the work is a PROTOCOL VIOLATION.

Closure is NOT optional. If the user says "end session" or you are wrapping up, you MUST run the full closure sequence. Skipping any step means the next agent starts blind.

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The Iron Chain

Prerequisite: You must establish a valid session context upon Wakeup before modifying any code.

Orientation → Synthesis → Strategic Gate → Red Team Audit → [Execution] → Loop Complete (Return to Orchestrator)

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Phase I: Orientation (The Scout)

Goal: Establish Identity & Context. Trigger: First action upon environment initialization.

1. Identity Check: Read any local orientation documents or primers provided by the user's environment.
2. Context Loading: Retrieve the historical session state (the "Context Snapshot" or equivalent state file) to understand what the previous agent accomplished.
3. Report Readiness: Output: "Orientation complete. Context loaded. Ready."

STOP: Do NOT proceed to work until you have completed Phase I.

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Phase II: Intelligence Synthesis

1. Mode Selection: Decide if you are doing standard documentation (recording ADRs) or exploratory research.
2. Synthesis: Perform your research. Aggregate findings into clear, modular markdown files in the project's designated learning/ or memory/ directory.