Update to Horizon Forge

{
  "description": "Discover overlooked industries, growth bottlenecks, and emerging economic opportunities through a structured global horizon scan. Use for candidate discovery and shortlisting before detailed forecasting.",
  "included_files": [
    {
      "relative_path": "agents/openai.yaml",
      "size_in_bytes": 225
    }
  ],
  "name": "horizon-scan",
  "skill_md_contents": "---\nname: horizon-scan\ndescription: Discover overlooked industries, growth bottlenecks, and emerging economic opportunities through a structured global horizon scan. Use for candidate discovery and shortlisting before detailed forecasting.\n---\n\n# Opportunity scan\n\nRead [operating instructions](../horizon-forecast/references/operating-instructions.md) and stages 1–4 of [research procedure](../horizon-forecast/references/research-procedure.md). If delegated, use the director's established scope and produce only the assigned memo. If standalone, write a brief plan before research and use global 5–10-year defaults unless instructed otherwise.\n\n1. Define the relevant buyer, activity, and market boundary. For a broad scan, seek 12–20 distinct segments; cover multiple economic drivers, regions, mundane services, and physical complements. Adapt the count to evidence and scope.\n2. For each candidate, identify a causal growth mechanism, current evidence, a plausible inflection, a binding constraint, and an observable contrary signal. Label speculative candidates.\n3. Seek overlooked complements of popular trends and transformations inside large existing industries. Distinguish low attention from low economic viability using a concrete comparator.\n4. Record a first- and second-order dependency map. Prioritize material tangents; maintain a watchlist for distant weak signals.\n5. Screen for paid demand, practical deployment within the horizon, economically meaningful scale, and distinctness from overlapping candidates. Use a known mature comparator to prevent a list comprised solely of exciting narratives.\n6. Return candidate cards, evidence URLs and dates, scope exclusions, a shortlist with research priorities, and discarded hypotheses with reasons. A preliminary shortlist is not a validated growth ranking; route full forecasts to [horizon-forecast](../horizon-forecast/SKILL.md).\n\nCard fields: segment; geography; buyer/budget; growth mechanism; observed signal; timing trigger; bottleneck; overlookedness comparator; best counterargument; baseline availability; evidence confidence; next decisive check.\n"
}