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Found 13 Skills
Build heads-up display (HUD) dashboards for AI coding agents — show context usage, active tools, running sub-agents, and task progress in real-time. Use when: monitoring AI agent activity, building developer tools for AI-assisted coding, creating status dashboards for agent workflows.
Analyze and clean up duplicate skills across vibe coding tools. Use when user asks to analyze skills, find duplicates, or clean up their skill collection.
One shared denylist of catastrophic shell commands (rm -rf on / or ~, dd/mkfs, sudo rm, fork bombs, curl|sh, git push --force, gh repo delete) enforced as a PreToolUse/pre-exec guard across every AI coding agent on the machine — Cursor, Claude Code, Codex, OpenCode, Pi, Hermes, Grok, Droid, Devin. Use when adding or tuning blocked-command patterns, wiring the guard into a new agent or a new machine, debugging why a command was (or was not) blocked, or when the user mentions command guard, guardrails, dangerous command hook, or PreToolUse safety.
Discover and install skills from multiple marketplaces for AI coding agents
Audit and optimise context window usage for AI coding tools (Claude Code, OpenCode, etc.). Estimates token breakdown, identifies waste (duplicate skills, overlapping rules, bloated instruction files, dirty git status, MCP server overhead), and provides actionable recommendations with projected savings. Use when the user says "context checkup", "reduce context", "check context", "context audit", "how big is my context", or when sessions feel sluggish.
Cross-tool compatibility workflow. Use when generating AGENTS.md files for compatibility with other AI coding tools, or creating tool-specific instruction files from CLAUDE.md.
Connects and configures the Render MCP server for AI coding tools—setup per tool (Cursor, Claude Code, Codex), authentication, workspace selection, tool catalog, and troubleshooting. Use when MCP is not configured, list_services() fails, the user asks about Render MCP setup, or an action skill needs MCP but it's not connected yet. Trigger terms: MCP, Render MCP, list_services, MCP setup, MCP server, OAuth, API key, Bearer token, mcp.render.com, workspace selection.
Set up the Deepgram MCP server for your AI coding tool. Checks whether the Deepgram CLI (dg/deepctl) is installed: if so, uses the local CLI MCP server (dg mcp) for full tool access; otherwise offers the hosted documentation MCP or suggests installing the CLI. Use whenever someone wants to install Deepgram's agentic tools, set up the MCP server, or connect their editor to Deepgram.
Methodology for effective AI-assisted software development. Use when helping users build software with AI coding assistants, debugging AI-generated code, planning features for AI implementation, managing version control in AI workflows, or when users mention "vibe coding," Cursor, Windsurf, or similar AI coding tools. Provides strategies for planning, testing, debugging, and iterating on code written with LLM assistance.
Engineering-discipline toolkit for non-technical users working with AI coders. Wields KISS, DRY, YAGNI, fail-fast, and idempotency as commands. Use when the user asks to audit, simplify, clean up, dedupe, or harden code; or says "make this simpler", "any duplicates?", "is this safe to run twice", "explain this app", "find dead code", "simplify the plan", or "find silent failures".
Multi-Harness Portability is the engineering discipline of writing agent skills, prompts, and configurations that work across every major AI coding harness — Claude Code, Cursor, Codex, Gemini CLI, OpenCode, and beyond.
Apply Andrew Ng's startup building principles and AI-accelerated development strategies from AI Fund's experience launching ~1 startup per month. Use when users ask about startup execution speed, AI coding tools for faster prototyping, agentic AI workflows, evaluating AI startup opportunities, or building AI applications. Triggers include questions about how to build startups faster, AI technology stack layers, where AI opportunities exist, implementing agentic workflows, or applying lessons from successful AI venture studios.