Phaselock: An AI Agent Control System Inspired by Parenting Techniques

Phaselock is an open-source Agent Skill that applies parenting techniques for autistic children to control AI coding agents. The developer observed that vague tasks cause both autistic children and AI agents to misinterpret instructions, leading to incomplete or incorrect execution.

Core Control Mechanisms

The system implements four specific control patterns:

• Explicit gates before action: Uses a BeforeToolUse hook that checks for an approved gate file on disk. No file, no write. The AI cannot proceed without architectural declaration first.
• Immediate feedback on mistakes: A PostToolUse hook runs static analysis after every file write (PHPStan, PHPCS, ESLint, ruff, etc.) and injects structured JSON results back into context. The AI sees exactly what broke and corrects itself before moving on.
• Constrained choices not open options: Complex features are broken into dependency-ordered slices. The AI works one slice at a time, with each slice halting for human review before the next begins.
• Rules that can't be rationalized away: Enforcement is mechanical via shell hooks that either allow or block. The AI's opinion about its own output is not evidence.

Technical Details

Phaselock works with Claude Code, Cursor, Windsurf, and anything that supports hooks and agent skills. The domain knowledge is shaped around Magento 2 and PHP, but the enforcement architecture is language-agnostic.

The current implementation has a scaling limitation: it loads all rules into context every session. At 80 rules this is manageable, but at 500 rules you're burning context before the task starts, and at 10,000 rules it's physically impossible.

Future Development: Writ

The developer is building Writ as a solution to the scaling problem. It's a hybrid retrieval system that figures out which rules matter right now and returns only those, achieving sub-10ms response times and 726x context reduction at 10,000 rules. The system is still experimental and undergoing stress-testing.

The developer notes that evaluation remains the hardest unsolved problem. Ground truth queries are synthetic at 80 rules, and it's unclear if retrieval quality holds on real queries from real sessions.