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Found 6 Skills
Manages Atlassian Jira and Confluence via the Rovo MCP Server. Handles MCP setup, OAuth authentication, and troubleshooting. Runs agentic project management: Confluence plans, Jira Epics with child tickets, agent team coordination, and resuming interrupted work from Jira state. Supports uploading images/attachments to Confluence pages via REST API. Reads and writes Confluence page comments (footer, inline, reply threads). Creates git branches linked to Jira tickets (GitHub and Bitbucket). Use this skill whenever the user mentions Jira, Confluence, Atlassian, tickets, epics, sprints, project boards, wiki pages, or Confluence spaces. Also trigger when the user wants to plan a project, break work into tasks, track progress, resume interrupted work, upload images to wiki pages, manage comments on Confluence pages, or create git branches linked to tickets — even if they don't mention Atlassian by name.
[MCP WRAPPER] Programmatically create/modify Godot scenes using Godot MCP tools. Orchestrates mcp_godot_create_scene, mcp_godot_add_node, mcp_godot_load_sprite into agentic workflows. Use when user requests scene generation/automation via MCP. Keywords MCP, scene automation, programmatic scene building, node hierarchy.
Build new AI method from scratch using the MTHDS standard (.mthds bundle files). Use when user says "create a pipeline", "build a workflow", "new .mthds file", "make a method", "design a pipe", or wants to create any new method from scratch. Guides the user through a 10-phase construction process.
Senior AI Product Manager. Expert in Probabilistic Strategy, Rapid Agentic Prototyping, and Hypothesis Generation for 2026.
Build AI-first applications with RAG pipelines, embeddings, vector databases, agentic workflows, and LLM integration. Master prompt engineering, function calling, streaming responses, and cost optimization for 2025+ AI development.
Build AI agents and agentic workflows. Use when designing/building/debugging agentic systems: choosing workflows vs agents, implementing prompt patterns (chaining/routing/parallelization/orchestrator-workers/evaluator-optimizer), building autonomous agents with tools, designing ACI/tool specs, or troubleshooting/optimizing implementations. **PROACTIVE ACTIVATION**: Auto-invoke when building agentic applications, designing workflows vs agents, or implementing agent patterns. **DETECTION**: Check for agent code (MCP servers, tool defs, .mcp.json configs), or user mentions of "agent", "workflow", "agentic", "autonomous". **USE CASES**: Designing agentic systems, choosing workflows vs agents, implementing prompt patterns, building agents with tools, designing ACI/tool specs, troubleshooting/optimizing agents.