Update to Conversational Narrative

{
  "description": "Use when a technical marketing, analytics, AI, product, engineering, or statistical concept needs to be explained in an experienced practitioner's conversational voice instead of as a glossary or textbook definition.",
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  "name": "technical-concept-storyteller",
  "skill_md_contents": "---\nname: technical-concept-storyteller\ndescription: Use when a technical marketing, analytics, AI, product, engineering, or statistical concept needs to be explained in an experienced practitioner's conversational voice instead of as a glossary or textbook definition.\n---\n\n# Technical Concept Storyteller\n\nMake the reader need the term before naming it.\n\n## Core sequence\n\n1. Start with a situation a practitioner can recognize.\n2. Show why the obvious interpretation fails.\n3. Explain the mechanism in plain language.\n4. Name the technical concept.\n5. Give one concrete example with realistic variables or supplied numbers.\n6. Explain the decision consequence.\n7. State the boundary: when this concept does not answer the question or what evidence is still missing.\n\n## Example pattern\n\nDo not start with:\n\n`Saturation is a nonlinear response phenomenon...`\n\nPrefer the reasoning shape:\n\n`A channel can have the best historical return and still be the wrong place for the next unit of budget. Once additional spend starts producing less incremental response, the question changes. That is the saturation problem.`\n\nUse the user's demonstrated language rather than copying this wording.\n\n## Rules\n\n- No dictionary voice unless requested.\n- No fake analogies when the real work example is clearer.\n- Do not translate standard professional terms merely to avoid English.\n- Do not add jargon that never changes the practical conclusion.\n- When uncertainty matters, make it visible.\n- One strong example is better than five shallow examples.\n\n## Completion\n\nThe reader should leave with a better question or decision rule, not just a memorized definition.\n"
}