public-trend-radar

name	public-trend-radar
description	Use when an agent needs public-channel trend discovery, trend cards, AI/technical trend signals, product/business trend signals, or open public sources as upstream context.

Public Trend Radar

Overview

Use this skill to discover public-channel trend signals and produce trend cards. Keep trend discovery separate from ordinary RSS daily reports, source governance, publishing, and final research synthesis.

Workflow Selection

• For public trend discovery, run subscription-research trend scan.
• For AI and technical trends, use --profile ai-tech.
• For product, launch, market, or product-management trends, use --profile product-business.
• For ordinary subscribed RSS daily news, use rss-ai-digest.
• For source quality and registry maintenance, use rss-source-curator.
• For deep research synthesis from evidence, use subscription-research-agent.

Runtime Command

Examples use subscription-research as a compatibility command. Before running commands, resolve the runtime command:

• When DIGESTPILOT_BACKEND_URL is available, product actions such as public trend fetch, trend scan, or WebUI-backed Radar refresh may use the Backend task API first, then read the resulting workspace output.
• If the Backend API is unavailable, keep using the local runtime command fallback below. Do not require WebUI, cloud, or a hosted service in generic Agent environments.
• Use DIGESTPILOT_RUNTIME_CMD when the environment provides a custom runtime command.
• Use digestpilot-runtime when it is available on PATH.
• Use subscription-research when only the legacy compatibility command is available on PATH.
• From a repository checkout without a linked command, replace subscription-research with node packages/research-cli/dist/src/cli.js.
• Run node scripts/doctor.mjs from the repository root to diagnose local runtime setup.
• If no runtime command is available but this repository or plugin package includes runtime source, run node scripts/bootstrap-runtime.mjs, then retry the command.

Core Command

Fetch live public-channel inputs into a local workspace:

subscription-research trend fetch-public \
  --profile ai-tech \
  --source-profile ai-models \
  --output-dir research-workspace/public-trend-radar/latest

Default public fetch coverage is intentionally small and reviewable. For ai-tech, it samples Hacker News discussion signals, GitHub repository search/topic activity, Hugging Face Daily Papers, and arXiv Atom results. For product-business, it samples product-leaning repository activity and public launch/discussion inputs; paper channels can be enabled explicitly when needed. Public fetch includes bounded fault handling: arXiv rate-limit or temporary-unavailable responses can retry once using Retry-After. Pass explicit public input files to trend scan when the user provides a custom source set.

For GitHub trend discovery, use repository search, topic search, and activity snapshots. Do not use GitHub releases as a Trend Radar input; releases belong to future Release Watch and upgrade-monitoring workflows.

Use --source-profile to select a public ingestion preset:

• ai-models: model releases, inference, benchmarks, model tooling, papers.
• ai-products: product launches, AI assistants, integrations, changelogs, product repos.
• industry: industry, infrastructure, regulation, market, and company signals.
• paper: Hugging Face Daily Papers, arXiv, paper discussions, benchmark papers.
• tip: practical engineering tips, workflows, HN discussions, agent/RAG usage.

Use --source-profile-file source-profiles.json when the user provides custom public source profiles. The file must be JSON:

{
  "profiles": [
    {
      "id": "custom-labs",
      "title": "Custom Labs",
      "category": "paper",
      "hackerNewsQueries": ["custom lab"],
      "githubRepoQueries": ["topic:custom-lab stars:>100"],
      "githubTopics": ["custom-lab"],
      "webUrls": ["https://example.com/lab/changelog"],
      "huggingFacePapers": true,
      "arxivPapers": false,
      "arxivQueries": [],
      "sourceWeights" 
         
         
      
       
         
         
      
    
  

Use githubRepoQueries and githubTopics for GitHub repository search and topic discovery. Use webUrls for official changelog, newsroom, research, launch, or documentation pages. These URLs are written into web-url-list.md alongside public discussion URLs, then consumed by trend scan.

Use sourceWeights and sourceRoles to tune how trend scan scores public signals for that profile. Source roles can be official, primary, secondary, community, or derived; official and primary sources carry stronger authority than community discussion or derived aggregators.

Generate trend cards from prepared public inputs:

subscription-research trend scan \
  --profile ai-tech \
  --source-profile ai-models \
  --web-url-list research-workspace/public-trend-radar/latest/web-url-list.md \
  --hacker-news-items research-workspace/public-trend-radar/latest/hn-items.json \
  --github-repo-signals research-workspace/public-trend-radar/latest/github-repo-signals.json \
  --hugging-face-papers research-workspace/public-trend-radar/latest/hugging-face-papers.json \
  --arxiv-papers research-workspace/public-trend-radar/latest/arxiv-papers.xml \
  --window 7d \
  --format markdown \
  --output research-workspace/public-trend-radar/latest/trend-cards.md

Generate product/business trend cards:

subscription-research trend scan \
  --profile product-business \
  --source-profile ai-products \
  --web-url-list launch-pages.md \
  --window 7d \
  --format json \
  --output trend-cards.json

When fixture or exported public data is available, trend scan can also consume public Hacker News item JSON, GitHub repository search signal JSON, Hugging Face Daily Papers JSON, and arXiv Atom XML:

subscription-research trend scan \
  --profile ai-tech \
  --source-profile paper \
  --hacker-news-items hn-items.json \
  --github-repo-signals github-repo-signals.json \
  --hugging-face-papers hugging-face-papers.json \
  --arxiv-papers arxiv-papers.xml \
  --format markdown

Output Guidance

Trend cards are upstream signals. They should explain what appears to be rising, why it matters, which public evidence supports it, and what downstream action is reasonable.

Use the structured card fields when writing summaries:

• what_changed: concise description of the observed public movement.
• why_it_matters: why the signal may matter to the target audience.
• suggested_action: downstream routing such as include-in-digest or add-to-watchlist.
• confidence_reason: short explanation of source count and primary/official evidence.

When writing data for the WebUI, preserve Radar intelligence fields in addition to trend cards: trend insights, ranking boards, ranking items, heat score, momentum delta, momentum label, sparkline points, source mix, rank reason, and evidence references. Radar output should support trend judgment and hot rankings, not only individual trend cards.

Do not rewrite trend cards into a daily report unless the user asks for a digest. If the user asks for a daily report, pass trend cards to rss-ai-digest or the active Agent as one input section.

Do not include private channels, personal browser history, private email, or private community data in this skill. Keep the first implementation limited to public channels.

Do not publish, notify, or update watchlists automatically. Use trend cards as reviewable output.

Profiles

• ai-tech: AI systems, models, agents, LLM infrastructure, papers, repos, datasets, benchmarks, developer tools, and engineering signals.
• product-business: AI products, launches, pricing, packaging, product positioning, company updates, integrations, growth signals, and product-management context.

Boundaries

This skill does not maintain RSS source registries, generate final research conclusions, or send notifications. It creates trend cards from public-channel signals for downstream Agent workflows.