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weak-signal-synthesizer — Claude Code skill: what it does & setup

Identifies weak signals across patents, research preprints, and GitHub repositories. Helps forecast emerging tech and market trends three to six months before they go mainstream.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add OneWave-AI/claude-skills --skill weak-signal-synthesizer -a claude-code
Open on GitHub

What weak-signal-synthesizer does

This skill directs the agent to spot early shifts before they reach tech media. It maps dots across unrelated fields, matching research preprints, patent filings, GitHub activity, and venture funding. The prompt relies on graph theory to uncover non-obvious links. Patterns must appear across at least three disconnected communities to qualify as an emerging signal.

Each report follows a fixed layout. The agent outputs the signal summary, supporting evidence, connection breakdown, a 3-to-6-month prediction, a confidence rating, and actionable next steps. Real predictive quality depends on supplied data: the skill provides the analytical framework rather than a live scraping pipeline.

What it helps with

  • connect patent filings with trending GitHub repositories
  • predict emerging niche developments 3 to 6 months out
  • identify patterns across disconnected developer communities
  • evaluate confidence scores for early market shifts

Example prompts for the agent

  • Analyze recent preprints and GitHub trending repos to spot weak signals in edge computing.
  • Map venture investments against patent filings to predict developer tooling trends in 6 months.
  • Review niche community discussions and highlight signals verified across three separate domains.

How to install weak-signal-synthesizer

1Skills CLI (Vercel)

npx skills add OneWave-AI/claude-skills --skill weak-signal-synthesizer -a claude-code

2Manually: put the files in place

~/.claude/skills/weak-signal-synthesizer/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/weak-signal-synthesizer/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about weak-signal-synthesizer

How do I install weak-signal-synthesizer in Claude Code?

Run npx skills add OneWave-AI/claude-skills --skill weak-signal-synthesizer -a claude-code. This installs the skill file to ~/.claude/skills/weak-signal-synthesizer/SKILL.md.

What does weak-signal-synthesizer do?

It detects emerging trends by finding graph-like connections between niche discussions, research preprints, patent filings, and venture funding. The skill then outputs 3-to-6-month forecasts with confidence levels.

What criteria does the skill use to validate a trend?

It requires a pattern to appear across at least three unrelated sources or communities before classifying it as a viable weak signal rather than an isolated outlier.

Source text

SKILL.md · MIT
---
name: weak-signal-synthesizer
description: 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.
---

# 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

```markdown
# 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!

© OneWave-AI · MIT · OneWave-AI/claude-skills

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