Convert logically accurate AI answers into felt, emotionally grounded explanations.
npx skills add https://github.com/wojons/je-ne-sais-quoi --skill je-ne-sais-quoi
Please help me install this Agent Skill. Skill: je-ne-sais-quoi Source: https://github.com/wojons/je-ne-sais-quoi/tree/main/skills/je-ne-sais-quoi Command: npx skills add https://github.com/wojons/je-ne-sais-quoi --skill je-ne-sais-quoi
It helps an AI move beyond logically correct answers that feel hollow, by teaching concepts with emotional and phenomenological weight through indirect illumination.
Ask the AI to apply the je-ne-sais-quoi architecture to a concept like time or grief and produce a logical explanation, a felt explanation, at least four situation-tests, and a hollow failure mode description.
High-intent search queries and answers about installing and using this skill.
Teach felt understanding by applying an architecture that weaves wisdom-tradition perspectives into a unified explanation, generates situation-based tests, and specifies hollow failure modes to differentiate genuine phenomenological grounding from pattern-matching.
A felt explanation converts logically accurate AI answers into emotionally grounded understanding by using indirect illumination, whereas standard answers often feel hollow because they lack the lived phenomenology required to convey meaning.
Test if an AI grasps untransmittable concepts by using situation-based scenario tests that reveal whether the model genuinely feels the concept, rather than relying on pattern-matching or technically correct but hollow definitions.
Use indirect illumination when advice, judgment, and meaning depend on lived phenomenology across cultures, specifically for untransmittable concepts like time, grief, urgency, trust, and impermanence that defy direct logical definition.
Identify detectable failure modes by specifying what a hollow, technically correct answer looks like, which creates a baseline to compare against responses that demonstrate genuine felt understanding through scenario tests.
Je-ne-sais-quoi requires YAML-identified skill metadata and an activation-time instruction set to generate felt explanations, situation-based tests, and explicit hollow failure mode descriptions without external dependencies.
wojonsExplain felt vulnerability from being seen and judged by others.
wojonsTeach AI to model grief as structural absence using situation-based tests.
MicrockAggregate insights from multiple wisdom and scientific traditions with synchronized output and per-tagging.
wojonsTeach AI to describe the felt threshold of irreversible decisions.
