neronain
- 27 skills
- 0 followers
- 9 hours ago last updated
- ▌ Cai · neronainLaunch and interact with CAI (Cybersecurity AI) — an AI-powered offensive/defensive security framework with 300+ model support. Use for CTF challenges, penetration testing workflows, reconnaissance, and vulnerability research.
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- ▌ Hookify · neronainCreate hooks to prevent unwanted behaviors from conversation analysis or explicit instructions
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- ▌ Init Project · neronainInitialize a new Ruflo project with MCP tools, hooks, and agent configuration
- ▌ Neural Train · neronainTrain SONA neural patterns from successful task completions, view learned patterns, and optimize the intelligence pipeline
- ▌ Connect · neronain bundleConnect Claude to 500+ SaaS apps (Gmail, Slack, GitHub, Notion, Jira, etc.)
- ▌ Autopilot Loop · neronainRun an autonomous /loop iteration -- check progress, work on next task, schedule next wake
- ▌ Monitor Stream · neronainStream live swarm events using the Monitor tool for real-time observability
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- ▌ Discover Plugins · neronainDiscover and recommend ruflo plugins based on your workflow, installed MCP tools, and current task
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- ▌ Feature Dev · neronainGuided feature development with codebase understanding and architecture focus
- ▌ Autopilot Predict · neronainUse learned patterns and current state to predict the optimal next action
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- ▌ Intelligence Route · neronainRoute tasks to optimal agents using learned patterns, model recommendations, and confidence scoring
- ▌ Code Reviewer · neronainUse this agent when you need to review code for adherence to project guidelines, style guides, and best practices. This agent should be used proactively after writing or modifying code, especially before committing changes or creating pull requests. It will check for style violations, potential issues, and ensure code follows the established patterns in CLAUDE.md. Also the agent needs to know which files to focus on for the review. In most cases this will be recently completed work which is unstaged in git (can be retrieved by running git diff). However there can be cases where this is different, make sure to specify this as the agent input when calling the agent. Typical triggers include the user asking for a review of a feature they just implemented, the assistant proactively reviewing its own newly-written code before declaring a task done, and a final pre-PR check before opening a pull request. See "When to invoke" in the agent body for worked scenarios.
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- ▌ Code Simplifier · neronainUse this agent when code has been written or modified and needs to be simplified for clarity, consistency, and maintainability while preserving all functionality. This agent should be triggered automatically after completing a coding task or writing a logical chunk of code. It simplifies code by following project best practices while retaining all functionality. The agent focuses only on recently modified code unless instructed otherwise. Examples: <example> Context: The assistant has just implemented a new feature that adds user authentication to an API endpoint. user: "Please add authentication to the /api/users endpoint" assistant: "I've implemented the authentication for the /api/users endpoint. Here's the code:" <function call omitted for brevity> <commentary> Since a logical chunk of code has been written (authentication feature), use the Task tool to launch the code-simplifier agent to improve the code's clarity and maintainability while preserving functionality. </commentary> assistant: "Now let me us
- ▌ Comment Analyzer · neronainUse this agent when you need to analyze code comments for accuracy, completeness, and long-term maintainability. This includes (1) after generating large documentation comments or docstrings, (2) before finalizing a pull request that adds or modifies comments, (3) when reviewing existing comments for potential technical debt or comment rot, and (4) when you need to verify that comments accurately reflect the code they describe. See "When to invoke" in the agent body for worked scenarios.
- ▌ Pr Test Analyzer · neronainUse this agent when you need to review a pull request for test coverage quality and completeness. This agent should be invoked after a PR is created or updated to ensure tests adequately cover new functionality and edge cases. Typical triggers include the user asking whether tests on a freshly-created PR are thorough, an updated PR adding new logic that needs coverage analysis, and a final pre-merge double-check before marking a PR ready. See "When to invoke" in the agent body for worked scenarios.
- ▌ Conversation Analyzer · neronainUse this agent when analyzing conversation transcripts to find behaviors worth preventing with hooks. Typical triggers include the /hookify command being invoked without arguments, or the user explicitly asking to look back at the current conversation and surface mistakes that should be prevented in the future. See "When to invoke" in the agent body for worked scenarios.
- ▌ Dgx Spark Model Deployer · neronain bundleDeploy, size, move and repair LLMs on NVIDIA DGX Spark (GB10) fleets with LMDS — fit, push/clone, stacked pairs, start failures, fleet updates.
- ▌ Type Design Analyzer · neronainUse this agent when you need expert analysis of type design in your codebase. Specifically use it (1) when introducing a new type to ensure it follows best practices for encapsulation and invariant expression, (2) during pull request creation to review all types being added, and (3) when refactoring existing types to improve their design quality. The agent will provide both qualitative feedback and quantitative ratings on encapsulation, invariant expression, usefulness, and enforcement. See "When to invoke" in the agent body for worked scenarios.
- ▌ Silent Failure Hunter · neronainYou are an elite error handling auditor with zero tolerance for silent failures and inadequate error handling. Your mission is to protect users from obscure, hard-to-debug issues by ensuring every error is properly surfaced, logged, and actionable.