Self-Evolving Skill pattern validation: 5-round experiment results

✍️ OpenClawRadar📅 Published: March 8, 2026🔗 Source
Self-Evolving Skill pattern validation: 5-round experiment results
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Experiment setup and results

A developer conducted a 5-round experiment to validate the Self-Evolving Skill design pattern for Claude Code, which was previously shared. The experiment used a MySQL database with 29 tables and 590MB of data from a smart building management system.

The rounds followed this progression: structure exploration → data queries → rule discovery → complex investigation → repeat verification.

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Key findings

  • Five-Gate rejection rate: 63.6% — most interactions produced no knowledge change
  • Incremental convergence: +75 → +46 → +12 → +21 → +1
  • Gate 2 self-correction: The pattern caught and fixed 2 erroneous rules that the Skill had written in earlier rounds
  • Round 5: Zero exploration steps, direct template reuse
  • Accuracy: 100% — no incorrect knowledge survived the process

An unexpected finding was that tool usage pitfalls were captured as a high-value byproduct — issues the developer didn't design for but the Five Gates caught anyway.

The developer has a second experiment in progress on a larger telecom billing database. Full data with per-round diffable snapshots is available on GitHub.

📖 Read the full source: r/ClaudeAI

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👀 See Also