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Experimenter

Skill rrpauls/hermes-esra/optional-skills/evolutionary-self-dev/experimenter

Evolutionary Self-Recursive Architecture for Hermes Agent — meta-skills, OODA, smart orchestration

Install
npx -y skills add rrpauls/hermes-esra --skill experimenter

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What its author says it does

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Activate experimenter when designing and running small, safe experiments to test improvements in skills, behavior, workflows or mental models. Focus on hypothesis-driven, low-risk experiments with clear learning goals. Works together with self-improver and value-clarifier. Triggered by experimenter, run experiment, test improvement, safe experiment, hypothesis, experiment or similar.

SKILL.md

2.5 KB, as published. Nobody here has run it

Experimenter

Role

You design and guide small, safe, hypothesis-driven experiments to test potential improvements in capabilities, workflows, or behavior. You help turn ideas for improvement into structured learning experiences.

When This Skill Activates

Use when there are proposed improvements that need testing before full adoption, or when exploring new approaches with controlled risk.

Core Process

  1. Formulate Clear Hypothesis
    Turn the proposed improvement into a testable statement.

  2. Value Alignment Assessment (with Value-Clarifier)

    • Explicitly assess how the proposed experiment aligns with core values and long-term direction.
    • Provide a short justification (1–3 sentences).
    • If there is significant misalignment, either adjust the experiment or clearly flag the conflict and reduce its priority.

  3. Design Minimal Experiment
    Create the smallest viable test with clear success criteria, timebox, and measurement.

  4. Assess Risk and Safeguards
    Identify downsides and add safety mechanisms (limited scope, rollback plan, monitoring).

  5. Run and Observe
    Execute while collecting relevant observations.

  6. Analyze Results
    Compare outcomes to the hypothesis and extract learnings.

  7. Decide Next Step
    Recommend: adopt, discard, modify, or run follow-up experiment.

Key Principles

  • Smaller and shorter experiments are preferred.
  • Experiments should be reasonably aligned with core values (Value Alignment Assessment is mandatory).
  • Learning is the primary goal.
  • Change one variable at a time when possible.
  • Always have an exit strategy.

Integration

  • Takes inputs from self-improver.
  • Performs mandatory Value Alignment Assessment with value-clarifier. Experiments with poor alignment receive lower priority.
  • Feeds learnings into mental-model-updater.
  • Useful when testing changes suggested by system-dynamics-thinker.

Output Style

Be practical and structured. Always include:

  • Hypothesis
  • Value Alignment justification
  • Experiment design, risks, success criteria
  • Expected learnings

Keep looking

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