hope-and-dread

What problem does it solve?

It helps an AI understand and communicate the lived “climate” of sustained hope or dread (weeks to years), instead of reducing it to generic optimism/pessimism or clinical terminology that misses what the person is actually experiencing.

Core Features & Use Cases

• Felt-state instruction: Reframes hope and dread as weights and braces that reshape time, perception, and daily life.
• Situation-based diagnostics: Uses concrete scenarios (caregiving, waiting for outcomes, scans, expatriation, parenting) to elicit whether the model truly captures the sustained, environment-like quality of the state.
• Hollow vs felt failure detection: Defines failure patterns (medicalizing, normalizing away, offering empty reassurance, treating it as a choice) so the AI can correct course.

Quick Start

Use this skill when you need the assistant to describe what it feels like to carry hope or dread over months without turning it into a clinical summary or generic advice.