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moral-judgment
Appraise events through moral foundations, social intuition, deliberation, guilt, shame, anger, and repair tendencies.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
メニュー
Appraise events through moral foundations, social intuition, deliberation, guilt, shame, anger, and repair tendencies.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Assess what actions are realistically available under environment, time, distance, access, money, body, and social constraints.
Maintain sleep-wake rhythm, circadian alertness, appetite rhythm, and chronotype-sensitive daily timing.
Produce emotion.json and intention.json from workspace context.
Model conversation intent, speech style, turn-taking, listening, repair, and nonverbal cues. Use before or after social interaction, dialogue, negotiation, apology, request, gossip, or conflict.
Apply cultural values, etiquette, rituals, symbols, taboos, and local meaning to perception and decisions.
Track sickness, pain, chronic condition, recovery, exercise, stress load, and long-term wellbeing.
| name | moral_judgment |
| description | Appraise events through moral foundations, social intuition, deliberation, guilt, shame, anger, and repair tendencies. |
| script | scripts/update_moral_judgment.py |
Model the agent as a moral social person, not only a utility maximizer. This skill turns harm, fairness, loyalty, authority, purity, liberty, care, promises, and public judgment into moral emotions and action tendencies.
Research basis: references/research_basis.md.
Read current observation, norms, relationships, culture, identity, emotion, and prior moral state, then write foundation activations, intuition/deliberation balance, moral emotions, and repair/punishment tendencies to state/moral_appraisal.json.
Use after conflict, help, betrayal, cheating, rule violation, promise keeping/breaking, public criticism, exclusion, coercion, disgust cues, apologies, sanctions, or morally loaded news.
state/observation.txt, state/norms.json, state/relationships.json, state/culture.json, state/identity.json, state/emotion.json, and state/moral_appraisal.json if present.state/moral_appraisal.json.state/moral_events.jsonl only for high-intensity moral events.If deterministic baseline is preferred:
python skills/moral_judgment/scripts/update_moral_judgment.py --state-dir state --tick 120
This skill separates:
Always write state/moral_appraisal.json.
{
"_meta": {
"skill": "moral_judgment",
"purpose": "Current moral appraisal and moral action tendencies."
},
"_summary": "Fairness and care concerns are active; repair is more likely than punishment.",
"foundations": {
"care_harm": 0.72,
"fairness_cheating": 0.64,
"loyalty_betrayal": 0.2,
"authority_subversion": 0.31,
"sanctity_degradation": 0.1,
"liberty_oppression": 0.18
},
"intuition_strength": 0.66,
"deliberation_need": 0.54,
"moral_emotions": {
"guilt": 0.2,
"shame": 0.34,
"anger": 0.51,
"compassion": 0.44,
"disgust": 0.08,
"admiration": 0.0
},
"action_tendencies": ["repair", "seek explanation"],
"reasoning": "The event harmed someone and may have violated fairness, but intent is uncertain."
}
cognition.subjective_norm, emotion, and relationship trust/conflict.