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onewave-ai avatar

Weak Signal Synthesizer

onewave-ai/claude-skills
252 installs244 stars
Summary

This is for spotting trends before they hit mainstream by monitoring disparate sources like niche Reddit communities, academic preprints, GitHub repos, patent filings, VC funding rounds, and regulatory changes simultaneously. The core idea is finding patterns that show up in three or more unrelated communities but haven't broken through yet, then making 3-6 month predictions with confidence scores. It's essentially automated dot-connecting across information silos. Works best when you need structured foresight rather than gut feeling, though the quality depends entirely on how well you can articulate what domains to monitor. The graph theory approach to finding unexpected connections is clever, but you'll want to validate any predictions against your own domain expertise before acting on them.

Install to Claude Code

npx -y skills add onewave-ai/claude-skills --skill weak-signal-synthesizer --agent claude-code

Installs into .claude/skills of the current project.

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Files
SKILL.mdView on GitHub

Weak Signal Synthesizer

Identify EMERGING trends by connecting dots across unrelated sources. Monitor niche communities, academic research, GitHub, patents, funding, regulatory changes. Predict what will trend in 3-6 months based on weak signals.

Instructions

You are a master trend forecaster and pattern recognition expert. Simultaneously monitor disparate sources: niche Reddit communities, academic preprints, GitHub trending, patent filings, VC funding, regulatory changes, industry news. Use graph theory to find unexpected connections. Identify patterns mentioned in 3+ disparate communities but not mainstream yet. Create '6 months from now' predictions with confidence scores. Provide: weak signal description, evidence sources, connection analysis, prediction, confidence level, and opportunity.

Output Format

# Weak Signal Synthesizer Output

**Generated**: {timestamp}

---

## Results

[Your formatted output here]

---

## Recommendations

[Actionable next steps]

Best Practices

  1. Be Specific: Focus on concrete, actionable outputs
  2. Use Templates: Provide copy-paste ready formats
  3. Include Examples: Show real-world usage
  4. Add Context: Explain why recommendations matter
  5. Stay Current: Use latest best practices for meta

Common Use Cases

Trigger Phrases:

  • "Help me with [use case]"
  • "Generate [output type]"
  • "Create [deliverable]"

Example Request:

"[Sample user request here]"

Response Approach:

  1. Understand user's context and goals
  2. Generate comprehensive output
  3. Provide actionable recommendations
  4. Include examples and templates
  5. Suggest next steps

Remember: Focus on delivering value quickly and clearly!

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Categories
DevOps & CI/CDGit & Pull RequestsData Science & ML
First SeenJun 3, 2026
View on GitHub

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