π―Skills30
threejs-game skill from natea/fitfinder
reddit-sentiment-analysis skill from natea/fitfinder
market-analyst skill from natea/fitfinder
Analyzes game concepts for monetization potential, ranking them by revenue opportunity and identifying top financial strategies.
demo-builder skill from natea/fitfinder
Orchestrates advanced distributed workflows using dynamic swarm topologies, enabling parallel research, development, and testing across specialized adaptive agents.
Analyzes product performance metrics, identifying key performance indicators and generating insights to optimize market fit and strategic decision-making.
Optimizes database performance for agent interactions by improving query efficiency, indexing, and data retrieval strategies in the FitFinder multi-agent system.
Aggregates and indexes reasoning strategies and agent metadata to enable intelligent cross-referencing and dynamic skill selection for multi-agent workflows.
Orchestrates multi-step workflows by chaining agent outputs sequentially, enabling complex data transformations and pipeline processing.
Manages persistent memory and retrieval patterns for AI agents using a structured database approach with advanced caching and indexing strategies.
Enables distributed neural network training and deployment across E2B sandboxes with flexible architectures and resource tiers.
Orchestrates multi-agent AI code reviews on GitHub PRs, performing comprehensive security, performance, and quality analysis with intelligent swarm coordination.
Generates and configures custom AI agent skills by analyzing project requirements and automatically constructing modular, reusable skill components.
Manages and synchronizes multiple GitHub repositories, handling submodule updates, cloning, and recursive repository interactions.
Orchestrates multi-agent collective intelligence with queen-led coordination, specialized workers, and robust consensus mechanisms.
Learns and adapts agent database configurations dynamically through intelligent plugin mechanisms to enhance multi-agent system performance.
Performs semantic vector search across agent documents using embeddings to retrieve contextually relevant information efficiently.
Automates GitHub project workflows by tracking issues, managing milestones, and generating progress reports for collaborative development.
Synthesizes complex market research data into actionable intelligence by systematically organizing and extracting strategic insights across multiple domains.
Manages Flow Nexus platform capabilities through comprehensive authentication, sandbox execution, app deployment, credit management, and coding challenges.
Coordinates and manages distributed AI agent workflows, dynamically allocating tasks and resources across a network of specialized agents to optimize collaborative problem-solving.
Automates the discovery, tracking, and strategic management of potential market entry points and customer engagement hooks for product development.
Orchestrates comprehensive software development through a systematic 5-phase methodology with multi-agent collaboration, test-driven design, and continuous quality validation.
Enhances agent database management by providing advanced querying, filtering, and metadata enrichment capabilities for AI agent repositories.
Orchestrates cloud-based AI agent swarms with event-driven workflows, intelligent coordination, and scalable multi-topology deployment.
Automates GitHub release processes, managing version tagging, release notes generation, and artifact publishing for software projects.
Validates and ensures the accuracy, reliability, and quality of AI-generated market research, product ideas, and audience segmentation outputs through systematic verification processes.
Automates GitHub workflow tasks like issue creation, PR management, repository synchronization, and submodule coordination using AI-driven orchestration.
Assists developers by dynamically matching AI coding partners to collaborate on software development tasks and provide real-time code suggestions.