Agent Architect Kit ↔ ThumbGate Bridge

Markdown agent memory entries are parsed by a deterministic importer that extracts mistakes and learnings, converts them into feedback signals, and regenerates PreToolUse prevention rules. This pipeline bridges static instruction edits to runtime enforcement for specific agent roles.

The migration process safely skips Session Log entries to avoid polluting the searchable lesson database with ephemeral task receipts. Running the integration import in dry-run mode first validates that only Mistakes and Learnings sections are targeted before executing the real import.

Feedback-to-rules regeneration works by feeding imported lessons into the same rule-generation pipeline as native feedback, creating PreToolUse hooks that enforce prevention rules before tool execution rather than after review. Rejection keywords flip entries negative so enforcement learns correctly.

Yes, npm and node are required dependencies to run the integration. The Skill relies on Node.js scripts to execute the deterministic parser, process the memory directory, and run the feedback-to-rules regeneration pipeline for targeted imports.

You can test memory migration by running the integration import in dry-run mode first for the architect-kit memory directory. This validates the parsed entries and feedback tagging without committing changes, ensuring auditable traceability before executing the real import and rule regeneration.

The best way to classify stakeholder feedback is by interpreting rejection-style keywords such as "rejected," "wrong," or "broken" to flip entries negative. This ensures the enforcement learns correctly from past mistakes and generates accurate PreToolUse prevention rules for blocked actions.