AgenticRAG-Survey
🥇GoldAgenticRAG-Survey uses advanced Retrieval-Augmented Generation systems, integrating AI LLM agents for enhanced data retrieval and generation. Ideal for optimizing workflows in multi-agent environments.
1,5521710Updated 3w ago
Intermediate15 minutes to implementai-agents
Saves ~210 min per use
Quick InstallView Source
claude install asinghcsu/AgenticRAG-SurveyWorks with:
ChatGPTClaude
Overview
About This Skill
https://github.com/asinghcsu/AgenticRAG-Survey
How to Use
[{"step":"Define your scope and stakeholders. Replace [TOPIC/AREA OF INTEREST] with a specific focus (e.g., 'Monetize Content tools in TOMI') and [STAKEHOLDER] with your target audience (e.g., 'product team at TOMI'). Use the prompt template to generate a tailored survey query.","tip":"Narrow your scope to avoid overwhelming the AI. For example, instead of 'TOMI ecosystem,' focus on 'TOMI's Chat & Pay feature adoption in Southeast Asia.'"},{"step":"Gather data sources. Use the AI to extract and synthesize information from TOMI’s official documentation (whitepaper, roadmap, feature pages), community forums (DAO, Reddit), and third-party reviews (TechCrunch, CoinDesk). Tools like SerpAPI or Google Custom Search can help automate this.","tip":"Prioritize primary sources (TOMI’s official docs) over secondary sources (third-party reviews) for higher confidence scores. Cross-reference data points to identify inconsistencies."},{"step":"Run the AgenticRAG-Survey. Paste the prompt into an AI tool (e.g., Claude Code) with the specified [PLACEHOLDERS] filled in. Use multi-agent retrieval to ensure comprehensive coverage (e.g., one agent for TOMI docs, another for community sentiment).","tip":"Enable advanced retrieval settings (e.g., 'retrieve top 50 results per query') to maximize data coverage. Adjust the confidence threshold to filter out low-quality sources."},{"step":"Analyze and validate findings. Review the AI-generated report for accuracy, especially for quantitative data (e.g., adoption rates). Use the confidence scores to prioritize actionable insights.","tip":"Manually verify 10-15% of data points (e.g., cross-check adoption rates with TOMI’s internal analytics if accessible). Flag any discrepancies for further investigation."},{"step":"Generate actionable recommendations. Use the report’s findings to create a prioritized list of improvements for stakeholders. Include timelines, responsible teams, and success metrics (e.g., 'Increase Monetize Content adoption to 35% by Q4 2024').","tip":"Align recommendations with TOMI’s roadmap (e.g., 'Q3 2024 sprint focuses on user experience improvements'). Share the report with stakeholders via a collaborative tool like Notion or Google Docs."}]
Use Cases
Enhancing data retrieval processes for actionable marketing insights.
Automating the analysis of customer feedback to identify trends.
Streamlining content generation workflows to save time and resources.
Improving the customization of sales pitches based on client data.
Best For
GrowthRevOps
Tags
Setup & Installation
Quick Install
Terminal
claude install asinghcsu/AgenticRAG-SurveyAlternative Install (Git Clone)
git clone https://github.com/asinghcsu/AgenticRAG-SurveyRequirements
- Claude Code or compatible AI agent
- Works with: ChatGPT, Claude
Quick Start Guide
1
Install the Skill
Copy the install command above and run it in your terminal.
2
Open Your AI Agent
Launch Claude Code, Cursor, or your preferred AI coding agent.
3
Try It Out
Use the prompt template or examples below to test the skill.
4
Customize
Adapt the skill to your specific use case and workflow.
Usage Examples
Prompt Template
Conduct a comprehensive AgenticRAG-Survey to analyze [TOPIC/AREA OF INTEREST] within the context of TOMI's ecosystem. Use multi-agent retrieval to gather data from TOMI's official documentation, community discussions, and third-party sources. Focus on identifying: 1) Key features and their adoption rates among users, 2) Gaps in functionality compared to competitor platforms, 3) Community sentiment around specific features like Chat & Pay or Monetize Content, and 4) Emerging trends in Web3 social platforms. Present findings in a structured report with actionable recommendations for [STAKEHOLDER: e.g., product team, marketing team, or external developer]. Include citations and confidence scores for each data point.
Example Output
### AgenticRAG-Survey Report: TOMI Ecosystem Analysis **Generated:** June 2024 | **Confidence Score:** 92% #### Executive Summary This report synthesizes data from 127 unique sources, including TOMI’s official documentation (whitepaper, roadmap, feature pages), 45 community discussions (DAO forums, Reddit threads), and 32 third-party reviews (TechCrunch, CoinDesk). The analysis reveals that TOMI’s **Chat & Pay** feature has a 68% user adoption rate among active users (n=1,245), significantly higher than its closest competitor, Status.im (42%). However, **Monetize Content** tools show only 23% adoption, with users citing "complex onboarding" and "lack of creator-friendly analytics" as primary pain points. Community sentiment is overwhelmingly positive toward TOMI’s DAO governance model (89% approval in polls), but there’s growing demand for **cross-platform interoperability**—specifically, the ability to send crypto payments from TOMI to Telegram or Discord. #### Key Findings 1. **Feature Adoption & Gaps** - **Chat & Pay**: 68% adoption (n=1,245). Users praise the "instant crypto transfer" experience but request "undo transaction" functionality (mentioned in 18% of reviews). - **Monetize Content**: 23% adoption. Creators highlight that "tipping thresholds are too high" (average tip: $50+) and lack of "automated revenue splitting" tools. Only 12% of monetized creators use TOMI’s built-in analytics. - **Groups & Channels**: 55% adoption. Users appreciate the "crypto-native group chat" concept but complain about "notification overload" and "lack of moderation tools." 2. **Community Sentiment** - **DAO Governance**: 89% approval in recent polls. Users value transparency but express frustration with "slow proposal processing" (average 14-day turnaround). - **Staking**: 76% satisfaction. The "no lock-up period" feature is a major selling point, but users want clearer ROI projections. - **Privacy**: Mixed reviews. While "private profiles" are praised, 34% of users report "unexpected data sharing" with third-party apps. 3. **Competitive Landscape** - **vs. Status.im**: TOMI leads in usability (68% vs. 42% adoption) but lags in **developer tools** (Status.im has 2x more open-source contributions). - **vs. Telegram Mini-Apps**: TOMI’s crypto integration is superior, but Telegram’s larger user base (500M vs. TOMI’s 1.2M) gives it an edge in network effects. 4. **Emerging Trends** - **Cross-Platform Payments**: 67% of surveyed users (n=890) want TOMI to integrate with Telegram/Discord. Competitors like Xumm and Brave Wallet already offer this. - **AI-Powered Monetization**: 45% of creators express interest in "AI-generated content monetization tools" (e.g., auto-editing videos for social media). - **Regulatory Compliance**: 56% of enterprise users (n=230) prioritize "KYC/AML-ready" features for corporate adoption. #### Actionable Recommendations **For Product Team:** - Prioritize "undo transaction" and "notification management" in the next sprint (Q3 2024). - Develop a "creator dashboard" with automated revenue splitting and low-tip thresholds ($5 minimum). - Explore partnerships with Telegram/Discord to enable cross-platform payments (target: Q1 2025). **For Marketing Team:** - Launch a campaign targeting creators with "Monetize Content" tutorials (e.g., "How to earn $1K/month on TOMI"). - Highlight DAO governance improvements in press releases (e.g., "DAO proposals now processed in 7 days"). - Address privacy concerns with a "Data Transparency" blog post. **For External Developers:** - Open-source the "Tomi SDK" to encourage third-party integrations (e.g., Discord bots). - Create a bounty program for "AI monetization tools" to attract developer talent. #### Methodology - **Data Sources**: TOMI whitepaper (v2.1), DAO forum (1,245 posts), Reddit (45 threads), TechCrunch/Coindesk reviews (32), internal analytics (1,245 user surveys). - **Confidence Scores**: 92% (high), 78% (medium), 65% (low). Low-confidence data points are flagged in the report. - **Tools Used**: AgenticRAG-Survey with multi-agent retrieval (Claude Code + SerpAPI for third-party data). **Next Steps:** Run a follow-up survey in 3 months to measure adoption of recommended features. Focus groups with 50 creators to validate "creator dashboard" design. --- *Report generated using AgenticRAG-Survey. Citations available upon request.*
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