Agent skill

startup-trend-prediction

Analyze 2-3 year historical trends in technology, market, and business models to predict 1-2 years ahead. Uses pattern recognition, adoption curves, and cycle analysis to identify timing windows and emerging opportunities. History is cyclical - products and markets follow predictable patterns.

majiayu000534★ · 1 repos on radarProfile →
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill startup-trend-prediction-vasilyu1983-ai-agents-public --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 13 KB
Bundled scripts: none
Path: skills/analysis/startup-trend-prediction-vasilyu1983-ai-agents-public/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Startup Trend Prediction Systematic framework for analyzing historical trends to predict future opportunities. Look back 2-3 years to predict 1-2 years ahead. **Modern Best Practices (Dec 2025)**: - Triangulate: require 3+ independent signals, including at least 1 primary source (standards, regulators, platform docs). - Separate leading vs lagging indicators; don’t overfit to social/media noise. - Add hype-cycle defenses: falsification, base rates, and adoption constraints (distribution, budgets, compliance). - Tie trends to a decision (enter / wait / avoid) with explicit assumptions and a review cadence. --- ## When to Use This Skill | Trigger | Action | |---------|--------| | "When should I enter this market?" | Run timing analysis | | "What's trending in [technology/market]?" | Run trend identification | | "Is this trend rising or peaking?" | Run adoption curve analysis | | "What comes after [current trend]?" | Run cycle prediction | | "Historical patterns for [topic]" | Run pattern recognition | | "2-3 year trends" or "predict 1-2 years" | Full trend prediction workflow | --- ## Quick Reference: Building a Trend View (Dec 2025) ### 1) Define the Decision - What decision are w

What's inside
Steps it walks through
  1. When to Use This Skill
  2. Quick Reference: Building a Trend View (Dec 2025)
  3. 1) Define the Decision
  4. 2) Collect Signals (Leading vs Lagging)
  5. 3) Hype-Cycle Defenses
  6. 4) Market Sizing Sanity Checks
  7. Adoption Curve Framework
  8. Rogers Diffusion Model
  9. Position Identification
  10. Gartner Hype Cycle Mapping
  11. Cycle Pattern Library
  12. Technology Cycles (7-10 years)
  13. Market Cycles (5-7 years)
  14. Business Model Cycles (3-5 years)
Ships with 1 file
  • metadata.json
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About this skill
What does the startup-trend-prediction skill do?

Analyze 2-3 year historical trends in technology, market, and business models to predict 1-2 years ahead. Uses pattern recognition, adoption curves, and cycle analysis to identify timing windows and emerging opportunities. History is cyclical - products and markets follow predictable patterns.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill startup-trend-prediction-vasilyu1983-ai-agents-public --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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