digest

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Get your personalized trend briefing based on profile domains.

⭐1stars🔀0forks📁View on GitHub🕐Updated Jan 4, 2026
[Web Research]

When & Why to Use This Skill

The Pattern Radar Digest skill is a sophisticated trend-monitoring agent designed to provide personalized, high-signal briefings. By leveraging a subagent architecture to analyze data from Hacker News and GitHub, it filters through the noise to deliver a curated narrative tailored to your specific professional domains. It excels at identifying intersections between different technologies and surfacing 'wildcard' insights that spark serendipitous discovery, transforming raw web signals into actionable recommendations for learning and building.

Use Cases

  • Personalized Industry Monitoring: Automatically track emerging trends and discussions on Hacker News and GitHub that specifically impact your tech stack or business domain.
  • Cross-Domain Innovation: Use the 'Wildcards' feature to discover unexpected technological shifts outside your primary focus, helping to inspire creative problem-solving and architectural innovation.
  • Strategic Learning & Development: Receive specific, actionable suggestions on which new tools to explore or which technical blog posts to read based on real-time community momentum.
  • Rapid Topic Evaluation: Perform quick scans of specific technologies (e.g., WebAssembly, Vector Databases) to gauge current developer interest and signal density before committing to a new project.
namepattern-radar:digest
descriptionGet your personalized trend briefing based on profile domains.

Personalized Trend Digest (Subagent-Driven)

This skill dispatches a Haiku subagent to generate your personalized trend briefing. Main context receives a curated narrative; subagent does the analysis.

Architecture

You (Opus) → Dispatch Haiku subagent → Subagent calls radar tools → Returns narrative
           ← Personalized briefing   ← Raw signals processed

How to Use

When user asks for trends, digest, or wants to know what's happening:

Step 1: Dispatch Digest Subagent

Use Task tool:
- subagent_type: "general-purpose"
- model: "haiku"
- prompt: "You are a personalized trend analyst. Generate a trend briefing for the user.

STEPS:
1. Call get_radar_digest() to fetch signals from HN and GitHub
2. Call get_intersections() to find domain overlaps
3. Call suggest_actions(focus: 'all') for actionable recommendations

OUTPUT FORMAT:
Return a 300-400 word personalized briefing with these sections:

## 🎯 Relevant to You
[2-3 patterns directly matching user's domains, with why they matter]

## 🌟 Wildcards (Serendipity)
[1-2 interesting signals OUTSIDE user's usual domains - unexpected discoveries]

## 💡 Suggested Actions
[2-3 specific actions: something to learn, something to build, something to explore]

Keep it conversational and actionable. Include specific links where helpful."

Step 2: Present the Briefing

Tell the user the subagent's narrative. Don't dump raw signal lists.

Serendipity Mode (Default)

IMPORTANT: Always include the Wildcards section. The whole point of pattern-radar is surfacing unexpected connections.

If user explicitly asks for "focused mode" or "only my domains":

  • Skip the Wildcards section
  • Mention: "I've filtered to just your domains. Say 'full digest' to include wildcards."

Quick Scan (Direct)

For quick topic scans, use tools directly (no subagent needed):

scan_trends(topic: "WebAssembly")

This returns raw signals - useful when user wants to explore a specific topic themselves.

Configuration

Help users configure their radar:

configure_sources(domains: ["TypeScript", "AI", "distributed-systems"])

Or for source weights:

configure_sources(hackernews_weight: 1.5, github_weight: 1.0)

Example Flow

User: What's trending that I should know about?

You: Let me generate your personalized trend digest...
[Dispatch Haiku subagent]

Subagent returns:
## 🎯 Relevant to You
**Edge Runtime Performance** is heating up - 3 HN discussions and 2 trending repos
about V8 isolates and cold start optimization. Given your TypeScript + serverless
background, this could affect your Lambda work.

**AI Code Review Tools** are seeing a surge. GitHub Copilot competitors like
Cursor and Continue are trending. Worth watching for your code-review plugin work.

## 🌟 Wildcards
**Game Engine Renaissance** - Godot 4.3 just dropped and HN is buzzing. Not your
usual domain, but the architectural patterns (ECS, hot-reload) might inspire
plugin design.

## 💡 Suggested Actions
- **Learn:** Read the Cloudflare Workers V8 isolate blog post (linked in signals)
- **Build:** Try adding AI-assisted review to your code-review plugin
- **Explore:** Check out Godot's plugin architecture for inspiration

User: Just show me AI stuff, skip the wildcards

You: [Call scan_trends directly]
Here are the AI-specific signals...