Research
Claude Code Plugin with AI research agent skills powered by MCP. 10 MCP tools, 5 agent skills, 6 AI research agents via RivalSearchMCP. Zero API keys.
npx -y skills add damionrashford/RivalSearch-Plugin --skill researchAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
Comprehensive multi-source research with academic depth. Searches web, social platforms, news, academic databases, and GitHub. Discovers papers, datasets, and open source implementations. Use when conducting research, literature reviews, or investigating any topic.
SKILL.md
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Research
Conduct comprehensive research on: $ARGUMENTS
Follow these steps precisely using RivalSearchMCP tools. Report progress after each step.
Step 1: Web Discovery
Use web_search for broad discovery:
- query: "$ARGUMENTS", num_results: 15, extract_content: true, follow_links: true, max_depth: 2
Identify the top 3-5 most relevant URLs. Note key themes and recurring sources.
Step 2: Social & Community Pulse
Use social_search to gauge community discussions:
- query: "$ARGUMENTS", platforms: ["reddit", "hackernews", "devto", "producthunt", "medium"], max_results_per_platform: 10, time_filter: "year"
Analyze what practitioners are saying. Note consensus, debate, and emerging opinions.
Step 3: News Coverage
Use news_aggregation for recent developments:
- query: "$ARGUMENTS", max_results: 15, time_range: "month"
Identify breaking news, announcements, and trend shifts.
Step 4: Academic Literature
Use scientific_research twice for peer-reviewed sources:
- operation: "academic_search", query: "$ARGUMENTS", max_results: 15, sources: ["semantic_scholar", "arxiv"]
- operation: "academic_search", query: "$ARGUMENTS survey OR review OR overview", max_results: 5
Identify the most cited papers, recent publications, key authors, and methodologies. Look for surveys that summarize the field.
Step 5: Datasets & Implementations
Use scientific_research for datasets:
- operation: "dataset_discovery", query: "$ARGUMENTS", max_results: 10
Use github_search for open source implementations:
- query: "$ARGUMENTS", sort: "stars", max_results: 10, include_readme: true
Step 6: Deep Content Retrieval
For the 3-5 most important sources from previous steps:
Use content_operations:
- operation: "retrieve", url: <selected_url>, extraction_method: "markdown"
For any key papers with accessible PDFs, use document_analysis:
- url: <paper_pdf_url>, max_pages: 10, extract_metadata: true, summary_length: 1000
Then analyze the most critical content:
- operation: "analyze", content: <retrieved>, analysis_type: "general", extract_key_points: true, summarize: true
Step 7: Compile Report
- Executive Summary — 2-3 paragraph overview of key takeaways
- Key Findings — Numbered list of the most important discoveries
- Web Intelligence — What mainstream sources reveal
- Community Sentiment — Practitioner discussions and opinions
- Recent Developments — News, announcements, trend shifts
- Academic Foundation — Key papers, methodologies, research threads, and key authors
- Datasets & Tools — Available datasets and open source implementations
- Deep Dive Insights — Detailed analysis from primary sources
- Contradictions & Gaps — Where sources disagree or information is missing
- Sources — Complete list of all URLs consulted
Use clean markdown. Cite sources inline with Source Name format.