Skill UI

Automate Composio’s Aero Workflow toolkit through the Rube MCP bridge, discovering current tool schemas with `RUBE_SEARCH_TOOLS`, validating connections, and dispatching schema-compliant calls to `RUBE_MULTI_EXECUTE_TOOL` for safe workflow operations.

A comprehensive client library for interacting with Azure Cosmos DB's NoSQL API in Rust. It enables performing core database operations, including CRUD (Create, Read, Update, Delete), patching, and managing globally distributed data. Ideal for building robust, data-intensive, and high-performance backend services on the Azure cloud platform.

Dispatch parallel agents to tackle independent failures concurrently so each investigator stays focused on one domain; review their summaries, check for conflicts, and run the full suite to integrate fixes faster than sequential debugging.

Guides multi-agent workflows through an iterative context retrieval loop—dispatching broad queries, evaluating relevance, refining criteria, and looping up to three times so sub-agents gather exactly the files they need without overwhelming limits.

Pyvene is a declarative framework designed for performing causal interventions on PyTorch neural networks. It allows researchers to conduct advanced experiments such as activation patching, causal tracing (ROME-style), and interchange intervention training (IIT). Use this library when you need to test causal hypotheses about model behavior, deeply interpret model components, or ensure reproducibility in advanced AI research.

Dispatching parallel agents lets you split independent investigations into focused prompts, coordinate isolated fixes concurrently, and review summaries for integration once each agent finishes.

Guides execution of implementation plans by dispatching isolated subagents per task, enforcing a spec-first then quality review loop, and preserving overall coordination context for faster, high-quality iterations.

A robust framework for orchestrating complex, multi-step coding tasks using multiple AI agents. It functions by first planning the entire project into a mission dependency graph (DAG), then dispatching specialized agents to isolated Git worktrees for parallel development. The system automatically monitors progress, handles merges, and generates structured, comprehensive reports detailing changes, completed tasks, and next steps.

A comprehensive guide and workflow for the post-containment phase of incident response. This process details systematic methods for mapping all persistence mechanisms, identifying malware artifacts, removing threats, resetting compromised credentials, and patching initial access vulnerabilities to ensure complete system eradication.

This skill implements a multi-factor scoring model to assess the criticality of IT assets. By weighting factors such as business function impact, data sensitivity, regulatory scope, and network exposure, it assigns a risk tier. This tier is then used to dynamically adjust the Service Level Agreements (SLAs) for vulnerability remediation, ensuring that organizations prioritize patching efforts on their most critical 'crown jewel' systems first.

This harness transforms standard code environments into fully persistent, autonomous agent systems. It leverages native features like scheduled tasks (Crons), remote dispatching, and structured memory storage (MCP) to enable continuous, self-directing automation. Ideal for building AI assistants that require long-term context, recurring workflows, and complex, multi-step operations, eliminating the need for external agent frameworks like AutoGPT.

This guide enforces a mandatory, multi-stage process for debugging complex software issues. It moves developers beyond merely patching symptoms by forcing them through Root Cause Investigation, Pattern Analysis, Hypothesis Validation, and proper Implementation with testing. It is crucial for solving production bugs, failed tests, and performance issues in a structured manner.