trend-intel
Scannednpx machina-cli add skill damionrashford/RivalSearch-Plugin/trend-intel --openclawTrend Intelligence
Analyze trends and news for: $ARGUMENTS
Follow these steps precisely using RivalSearchMCP tools. Report progress after each step.
Step 1: Breaking News Scan
Use news_aggregation twice to establish recency and trajectory:
- query: "$ARGUMENTS", max_results: 15, time_range: "week"
- query: "$ARGUMENTS", max_results: 15, time_range: "month"
Compare weekly to monthly volume. Is coverage accelerating, steady, or declining?
Step 2: Web Context
Use web_search twice for broader context:
- query: "$ARGUMENTS trends 2025 2026", num_results: 15, extract_content: true
- query: "$ARGUMENTS emerging growth adoption", num_results: 10, extract_content: true
Capture analysis from non-news sources (blogs, industry sites, company announcements).
Step 3: Social Signal Measurement
Use social_search twice to measure community momentum:
- query: "$ARGUMENTS", platforms: ["reddit", "hackernews", "producthunt", "devto", "medium"], max_results_per_platform: 15, time_filter: "month"
- query: "$ARGUMENTS", platforms: ["reddit", "hackernews"], max_results_per_platform: 15, time_filter: "year"
Compare recent (month) vs historical (year) volume. Note sentiment shifts, new voices, and debate intensity.
Step 4: Developer Adoption Signals
Use github_search twice:
- query: "$ARGUMENTS", sort: "stars", max_results: 15, include_readme: true
- query: "$ARGUMENTS", sort: "updated", max_results: 15
Compare established projects (stars) vs active development (updated). Note star counts, contributor numbers, and issue activity.
Step 5: Academic Foundation
Use scientific_research:
- operation: "academic_search", query: "$ARGUMENTS", max_results: 10, sources: ["semantic_scholar", "arxiv"]
Is there peer-reviewed research driving this trend? How recent are the publications?
Step 6: Deep Dives
For the 3 most insightful articles or reports found, use content_operations:
- operation: "retrieve", url: <article_url>, extraction_method: "markdown"
- operation: "analyze", content: <retrieved>, analysis_type: "general", extract_key_points: true, summarize: true
For the top 2-3 companies or projects driving this trend:
- Use
map_websitewith url: <player_url>, mode: "research", max_pages: 5, max_depth: 1
Step 7: Compile Trend Report
- Headlines — Top 3-5 stories in bullet form with one-line summaries
- Key Developments — Expanded coverage of the most significant stories (2-3 paragraphs each)
- Velocity Indicators — Table with metrics:
Signal Measurement Direction News frequency X articles/week Accelerating/Steady/Declining Social mentions X threads/month ... GitHub stars Top repo: X stars ... Academic papers X papers in last year ... - Community Pulse — What practitioners and the public are saying
- Maturity Assessment — Nascent / Emerging / Growing / Mainstream / Mature / Declining
- Key Players & Catalysts — Who and what is driving adoption
- Trajectory Projection — Bull case vs bear case with evidence
- What to Watch — Upcoming events, expected announcements, early signals to track
- Sources — All URLs consulted
Keep it concise but data-rich. Use clean markdown with inline citations Source Name.
Source
git clone https://github.com/damionrashford/RivalSearch-Plugin/blob/main/skills/trend-intel/SKILL.mdView on GitHub Overview
Trend Intelligence analyzes breaking news and market shifts by measuring velocity across web, social, news, GitHub, and academic signals. It generates digest-style updates and trajectory reports to help you identify trends early and monitor developments.
How This Skill Works
Trend Intelligence follows RivalSearchMCP steps: Step 1 scans breaking news with news_aggregation to compare weekly vs monthly coverage; Step 2 gathers broader context via web_search; Step 3 measures social momentum with social_search; Step 4 evaluates developer activity using github_search; Step 5 checks scholarly foundations with scientific_research; Step 6 performs deep-dives with content_operations and maps key players with map_website; Step 7 compiles a concise Trend Report featuring headlines, developments, velocity indicators, and projections.
When to Use It
- When tracking breaking news on a topic or market
- When identifying nascent or accelerating trends across sources
- When monitoring velocity across web, social, and academic signals
- When evaluating developer adoption signals and project activity
- When preparing evidence-based trend reports for stakeholders
Quick Start
- Step 1: Define the topic with the argument hint (topic, technology, market, or trend to track)
- Step 2: Run Step 1-3 to establish news digest and context (news_aggregation, web_search, social_search) and compare velocity
- Step 3: Run Step 4-7 to gather adoption signals, academic foundations, and compile the Trend Report
Best Practices
- Define the exact topic or trend using the argument hint to sharpen scope
- Run weekly and monthly comparisons to gauge velocity and trajectory
- Corroborate findings across at least three source types (news, web, social, GitHub, academia)
- Note sentiment shifts, key voices, and debate intensity over time
- Time-stamp sources and document data provenance for traceability
Example Use Cases
- Monitor generative AI tooling adoption across enterprises and research labs
- Track edge AI and autonomous systems deployment in manufacturing
- Follow climate-tech investment momentum and policy developments
- Assess quantum computing research momentum and leading project activity
- Observe open-source security tooling trends and community engagement
