Check code and agent outputs, track reliability scores, and roll back changes that fail a chosen threshold. Includes quality reports, live monitoring, and integration with automated build and deployment workflows.
Set up RuView sensing nodes by building and flashing ESP32 firmware, configuring WiFi and the receiving address, and checking serial logs. Diagnose missing CSI streams, the WiFi signal measurements sent by sensing nodes.
Verify RuView changes with Rust and Python tests, output hashes that detect processing changes, and firmware hash records. Packages test logs and audit evidence into a witness bundle that recipients can check with a single command.
Coordinate multiple AI agents with agentic-flow to run tasks in parallel or through ordered stages. Configure shared memory, team structure, workload distribution, retries, and task reassignment, then monitor how the group performs.
Organize software releases on GitHub, from version suggestions and release notes to testing, builds, and deployment. Coordinate multiple packages or repositories, roll changes out in stages, and configure rollback to restore an earlier release when problems occur.
Coordinate named agent teams on Grok Build using Ruflo MCP tools or a command-line message bus. Organize design, coding, testing, and review into ordered steps, with team-specific messages, status tracking, and shutdown.
Create a JSON theme preset for Ruflo Console Theme Studio from a visual brief. Adjust six colors, animation speed, and decorative layers while keeping text readable and success, warning, and failure states visually distinct.
Turn complex requests into actionable plans with smaller tasks, dependencies, assigned agents, and time estimates. The skill identifies work that controls the completion date, outlines risks and contingencies, and defines measurable success criteria.
Help design quorum management for distributed systems, where multiple nodes must agree on decisions. Covers adapting participation thresholds and voting weights to network conditions, performance, and failures, plus membership changes, validation, and rollback.
Implement and manage Raft, a method for keeping distributed servers in agreement. Covers leader election, log replication, node membership changes, and recovery after network disruptions to maintain consistent state across the cluster.
Check whether an application is ready for production by finding unfinished code and testing real database and API connections. Review performance under load, authentication, environment settings, and deployment behavior to identify gaps before release.
Coordinate a team of AI agents by setting direction, assigning responsibilities, allocating resources, and tracking progress. Support hierarchical decisions, group consensus, and emergency control while recording shared state and preparing handovers to keep work moving.
Manage GitHub pull requests, which are proposals to merge code changes, from creation through review, testing, conflict resolution, and merging. Coordinate multiple agents to divide review work and track progress across the process.
Analyze application and system performance to find bottlenecks, the points that slow processing. Use resource usage and performance data to plan improvements to resource allocation, load balancing, caching, and algorithms, then compare results after changes.
Connect work from multiple AI agents to GitHub Projects. Synchronize task cards and statuses, assign work based on expertise and workload, and generate progress reports so teams can track assignments, priorities, and blockers on shared boards.
Improve existing code through repeated cycles of testing, implementation, and refactoring. The skill covers performance bottlenecks, error recovery, code coverage, and documentation, helping developers refine behavior and structure while keeping tests passing.
Turn specifications into pseudocode, a language-independent outline of program logic. Define data structures, handle edge cases, analyze time and memory requirements, and document design patterns and optimization opportunities before implementation.
Create and improve GitHub Actions workflows that automate building, testing, and deployment. The skill covers testing across multiple environments, dependency caching, build output management, and security settings such as limited permissions and protected deployment environments.
Analyze large matrices before solving linear systems. Check structure and numerical stability, recommend preprocessing and solver settings, estimate selected solution values without a full solve, and assess convergence, memory use, and computational cost.
Analyze networks of people, web pages, or systems using PageRank, a method that scores importance from connections. Identify influential nodes and communities, generate personalized recommendations, and examine communication bottlenecks to guide network improvements.
Choose coding challenges matched to a learner’s level and goals within Flow Nexus. Validate submissions, review solution quality and efficiency, and track progress through rankings, achievements, badges, and challenge completion rewards.
Benchmark distributed consensus protocols, methods computers use to agree on shared results. Compare processing rates, response times, scaling behavior, and resource usage across Byzantine, Raft, and Gossip, then identify bottlenecks and potential tuning changes.
Coordinate groups of AI agents across multiple GitHub repositories. Analyze dependencies, organize shared updates and refactoring, run tests, and create linked pull requests so related projects can be changed together.
Manage payment permissions for AI agents with spending caps, expiration dates, and merchant rules. Use cryptographic signatures to verify authorization, coordinate approval from multiple agents for high-value purchases, and track or revoke payment permissions.
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