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Planned

Daily Contract Pulse

Persona Crypto Trader / On-Chain Analyst / Project Founder Wants to monitor key token contracts to track investor behavior, market sentiment, and unusual activityβ€”but lacks time or tools to analyze on-chain data consistently. Problem On-chain activity around a token contract can signal critical shifts (e.g., whale moves, sudden sell-offs), but: Manually checking dashboards (e.g., Etherscan, Dune) is time-consuming. Insights are often buried in raw data. There's no lightweight, daily digest summarizing contract-level trends. Missed movements can lead to delayed decisions or missed opportunities. Solution Create a Daily Contract Pulse agent that delivers concise, high-signal summaries for any token contract. Workflow: User submits a contract address (via UI or bot). System tracks and analyzes contract activity daily. Daily digest includes: Buy/sell volume breakdown Whale movements (e.g., top 10 wallets accumulating/distributing) Holder delta (net new holders) Standout transactions (e.g., large swaps, smart contract interactions) Delivery options: Email / Telegram / In-app Optional webhook or Notion export (for teams)

Questflow About 2 months ago

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New Feature

Auto-Request Feedback

Persona Product Manager / Community Lead / Indie Builder Motivated to build better products by staying close to early users, but lacks time and structure to consistently collect and prioritize user feedback across public platforms like Twitter/X. Problem Users often reply to product announcement or update tweets with complaints, bugs, or feature suggestions. However: These replies are scattered, unstructured, and hard to track. Valuable feedback often gets buried or missed. There's no quick way to prioritize input based on who said it (e.g. power users, influencers). Teams lack a systematic way to turn replies into actionable insights. Solution Build an Auto-Request Feedback agent that works as follows: Trigger: After a product update or prompt tweet is posted, the system automatically tracks replies and quote tweets. Collection: Gathers all relevant user replies containing feedback, suggestions, or complaints. Prioritization: Uses engagement metrics (likes, retweets) and user metadata (follower count, prior interactions) to rank replies by influence and relationship. Processing: Clusters similar feedback. Identifies themes (e.g. bugs, usability, feature request). Output: Generates an actionable report with: Ranked list of user feedback Suggested product responses or actions Option to one-click reply or acknowledge in-thread.

Questflow About 2 months ago

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New Feature

Completed

Questflow Builder Platform

Persona Independent developers, AI/automation enthusiasts, and solution builders who want to contribute to and benefit from the AI agent economy. They are technically capable but seek a streamlined way to build, deploy, and monetize agents or agent-based applications within a larger ecosystem. Problem Currently, there is no dedicated platform that allows these builders to easily create, configure, and publish their own AI agents, tools, or agent swarms (multi-agent workflows) in a way that integrates seamlessly with Questflow’s orchestration layer. This limits innovation, slows down ecosystem growth, and creates a bottleneck in scaling use cases and onboarding new contributors. Solution The Questflow Builder Platform will empower builders to independently create, test, and deploy tools, agents, and multi-agent swarmsβ€”without relying on core team intervention. This platform will: Offer modular and reusable components for building agents and tools Provide templates and a visual interface for configuring multi-agent swarms Include publishing tools to contribute to the Questflow marketplace/ecosystem Integrate with Questflow’s orchestration protocol and economic layer for monetization Enable versioning, collaboration, and testing environments for faster iteration

Questflow About 2 months ago

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Infrastructure

Smart-Style Social Engagement Bot

Persona: Thought leaders, and community managers looking to stay active and engaging on X without spending hours manually interacting. Problem: Maintaining a consistent and authentic presence on X is essential for growth, but: Writing thoughtful replies and quote tweets is time-consuming Engagement drops during busy periods Outsourcing social interaction risks losing brand voice and authenticity Solution: Smart-Style Social Engagement Bot keeps your social voice active and on-brand by: Learning your unique tone and style from past posts Drafting smart, context-aware replies, likes, and quote tweets Letting you review and approve scheduled interactions in one place

Questflow About 2 months ago

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New Feature

Cross-Channel Community Digest

Persona: Community managers, product teams, and project founders who need to stay on top of fast moving conversations and sentiment across multiple platforms to make timely decisions and improve engagement. Problem: Important feedback, trends, or sentiment shifts often get buried across fragmented channels like Twitter, Discord, Telegram, and onchain activity. Manually monitoring and summarizing this data: Takes too much time Requires context switching Risks missing key signals that could impact product or comms strategy Solution: Cross-Channel Community Digest automates intelligence gathering by: Scraping Twitter, Discord, Telegram, and on-chain events Analyzing sentiment and extracting engagement metrics Generating a concise, actionable brief with a pre-drafted summary ready for internal reports or public updates

Questflow About 2 months ago

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New Feature

Planned

Autonomous Airdrop Manager

Persona: Crypto project founders or marketing leads who want to incentivize community engagement and loyalty through regular airdrops without spending excessive time on manual tracking, reward distribution, or community updates. Problem: Manually managing airdrops is time consuming and error prone. Teams often need to: Export top token holder data from on-chain explorers Manually batch and distribute rewards Write Twitter threads or announcements to maintain transparency This process lacks automation, increases operational risk, and slows down engagement. Solution: Autonomous Airdrop Manager automates the entire airdrop lifecycle: Takes weekly snapshots of top-N token holders Batches and sends airdrop rewards automatically Publishes a live, auto-updated Twitter/X thread explorer to ensure transparency and real-time community engagement

Questflow About 2 months ago

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New Feature

Web-Based Form Auto-Fill Agent

Objective Develop an AI-powered agent that can complete tasks on behalf of users when integrated services do not provide sufficient APIs. Specifically, this agent will automate form-filling within web browsers, ensuring a seamless and efficient user experience. Key Features Automated Form Completion Detects input fields on web pages dynamically. Identifies required information based on field labels and context. Auto-fills forms using predefined or dynamically extracted data. Smart Data Extraction & Interpretation Scrapes relevant data from available sources (e.g., user databases, past inputs, or web content). Uses AI/LLM-based reasoning to determine the most appropriate values. Customizable Rules & User Overrides Allows users to define rules for auto-filling specific fields. Provides an option for manual verification before submission. Cross-Website Compatibility Works on multiple websites, even those without structured APIs. Uses computer vision and NLP techniques to understand form layouts. Expected Impact This AI agent will significantly reduce manual effort in repetitive form-filling tasks, improving productivity and minimizing human errors in web-based workflows.

Questflow 3 months ago

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New Feature

Automated Document Processing & Review Agent

Problem Statement Reviewing and processing documents manually leads to inefficiencies, errors, and delays. Automating document validation can improve accuracy and speed. Why This is Needed Manual Review is Error-Prone – Large volumes of data increase the chance of oversight. Verification is Time-Consuming – Checking reports and validating information slows down operations. Compliance & Auditability – Ensuring adherence to policies and regulations is crucial. Solution Develop an AI-powered document processing agent that automates verification: Form & Document Analysis: Extracts and processes data from spreadsheets, Word documents, and PDFs. Automated Auditing: Cross-checks reports and validates against predefined requirements. Detects inconsistencies and compliance issues.

QF User 4 months ago

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New Feature

Office & Productivity Automation Agent

Problem Statement Office workflows, such as scheduling meetings, summarizing messages, and task tracking, are time-consuming and require manual effort. An AI-powered assistant can streamline these tasks. Why This is Needed Meeting Coordination is Tedious – Finding mutual availability and booking meetings is time-consuming. Information Overload – Emails and messages contain too much data for manual processing. Task & Workflow Optimization – Manual tracking of tasks leads to inefficiencies. Solution Develop an AI office automation agent that enhances productivity: Calendar Booking: AI automatically schedules meetings based on availability. Email & Message Summary: Extracts key insights from long emails for quicker decision-making. Task Reminders & Workflows: Suggests next steps, assigns tasks, and tracks completion.

QF User 4 months ago

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New Feature

Completed

AI-Powered Social Media Engagement

Problem Statement Manually managing social media interactions is time-consuming, and missing key mentions or trends can reduce engagement. Automating responses, trend analysis, and user interactions improves efficiency and brand presence. Why This is Needed Real-Time Engagement – Responding quickly to mentions and trends is critical for visibility. Scalability – Manually liking, replying, and following users is inefficient for large accounts. On-Chain Social Actions – Some interactions require blockchain-based transactions, like airdrops or tipping. Solution Develop an AI social media agent that automates engagement: Automated Twitter/X Actions: Detect @ mentions and reply based on sentiment analysis. Auto-like, retweet, or follow relevant users. Execute on-chain actions, such as sending token rewards. Trend Monitoring: Track emerging discussions and proactively engage with relevant posts.

QF User 4 months ago

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New Feature

Crypto Trading Automation Agent

Problem Statement Managing crypto trading manually is inefficient, as market conditions change rapidly. Delayed responses can lead to missed opportunities and increased risks. An automated AI-driven trading system can enhance decision-making and optimize trade execution. Why This is Needed Market Volatility – Prices fluctuate constantly, requiring real-time monitoring and execution. KOL & Market Signal Tracking – Insights from KOLs and trading signals need instant processing. Risk Management – Manual execution increases the risk of poor decisions and delayed reactions. Solution Develop an AI-powered crypto trading agent that automates trading actions: Market-Driven Trading: Monitor KOL recommendations and market trends to execute automatic buy/sell orders. On-Chain Actions: Automate airdrops, token transfers, staking, and yield farming based on predefined conditions. Risk Management: Set stop-loss, take-profit limits, and trading strategies to protect assets.

QF User 4 months ago

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New Feature

KOL Campaign Management AI Agent

Problem Statement Managing KOL collaborations involves multiple repetitive and time-sensitive tasks, such as outreach, tracking, verification, and payment processing. Manual execution is inefficient, prone to delays, and difficult to scale. Why This is Needed Time-Consuming Communication – Reaching out to multiple KOLs via email or DM, following up for drafts, and chasing post links takes a lot of effort. Tracking & Validation Complexity – Manually verifying whether KOLs have posted on time, tracking engagement, and ensuring compliance is inefficient. Payment Bottlenecks – Delayed or incorrect payments due to manual approval processes create friction in collaboration. Solution Develop an AI-powered KOL automation agent that streamlines the entire campaign workflow from outreach to payment: KOL Outreach & Communication 1.1 Automated Email & DM Outreach: Identify and reach out to KOLs based on predefined criteria. Send personalized campaign details & collaboration requests via email or DM. 1.2 AI Follow-Ups: Automatically remind KOLs to submit their drafts, revisions, and final posts. Content Tracking & Validation 2.1 Draft Collection & Approval: Automatically collect and organize submitted drafts for review. 2.2 Post Tracking: Monitor when KOLs publish their content. Verify post links and check for required hashtags, mentions, or tags. Analyze engagement metrics (likes, comments, shares). Payment Automation 3.1 Post Verification Before Payment: Ensure KOLs meet campaign requirements before releasing payments. Detect fraudulent activity or missing deliverables. 3.2 Auto-Process Payments: Initiate crypto or fiat payments based on contract terms. Integrate with payment platforms (e.g., USDT, PayPal, bank transfers). Execution & Delivery Dashboard for campaign tracking (status updates, reminders, approvals). API integration with social media platforms and payment providers. Custom AI chat agent for handling real-time KOL communication.

QF User 4 months ago

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New Feature