@pagoda111king

skill-evolver-pro automates skill optimization through data analysis and generates improvement strategies via a state machine, persistent storage, and 6-stage pipeline. supports interruption recovery and audit logging but lacks concrete error handling and specific invocation triggers.

autonomous-learning-cycle proposes a 17-minute feedback loop for autonomous task execution, pattern extraction, confidence scoring, and skill generation with daily/weekly reflection. implementation details are vague and core algorithms lack concrete step-by-step procedures.

auto-improver claims to be a self-evolving ai agent with a 17-minute learning loop, but the skill.md provides no actionable procedure, no concrete inputs or outputs, and no recovery logic. marketing material disguised as documentation.

auto-improver-pro claims self-optimization via 17-minute feedback loops but lacks concrete procedural steps, decision logic, and failure handling. the markdown mixes marketing copy with bash examples that don't specify actual inputs or outputs.

Lightweight ETL pipeline orchestrator with lifecycle hooks, bundle execution, stage retry, timeout control, and built-in transformers. 26 tests, 100% pass rate.