@danielfoojunwei

auto-feedback analyzes execution logs, detects performance regressions, auto-generates regression tests, and produces signed improvement reports. operates standalone or integrates with intent-engineering and dark-factory for richer analysis across repeated cycles.

agentic-wireless-manager provides detailed steps for network scanning, signal scoring, and SAC-LTC inference across macOS, linux, and windows, but lacks concrete error handling, fallback logic, and validation steps between procedural stages.

agent-see converts websites and saas products into agent-executable bundles through a multi-stage pipeline. covers conversion, verification, launch artifacts, plugin packaging, and deployment orchestration with explicit output artifacts and status dashboards at each step.

intent-engineer describes a meta-framework for agent self-governance and multi-skill orchestration, but remains largely conceptual. the skill reads as architectural vision rather than actionable procedure, with minimal concrete trigger phrases and no documented failure modes.

Buildable Bring Your Own Context system for AI agents. Use for: creating user-owned or org-owned context vaults, scaffolding typed memory systems, generating...