Use when the user wants to manage his VPS servers and the AI agents running inside them — connecting, deploying, monitoring, restarting, and operating remote hosts and their agents. Triggers on VPS, server management, remote host, SSH into server, manage my servers, agents on the server.

Provision a hardened SELECT-only Postgres role so AI agents can safely read a production database. Works on Supabase and any Postgres. Use when the user wants agents to query prod data, says "read-only role", "safe prod DB access for agents", or is tired of running SQL by hand for agents. Differentiator: this skill CREATES the role and wiring; day-to-day querying belongs in a project-local skill.

Launch OpenAI Codex CLI as a subagent (ChatGPT subscription auth, no API key). Use when delegating a self-contained coding task to Codex from another agent — parallel implementation work, a second opinion, or an independent verification pass.

Make an AI agent run on a schedule, loop, or interval — cron, heartbeats, recurring autonomous checks. Use for "run every N minutes", "schedule a task", "run on a loop", "heartbeat". Covers external clocks (Claude Code, Codex, Pi) vs Hermes' built-in scheduler.

Use when the user (or a sibling skill via --wt flag) wants to spin up an isolated git worktree for a task — wraps the worktrunk `wt` CLI when present, falls back to native `git worktree`, switches the Bash session cwd into the new worktree, auto-applies docker isolation when profile present (skip with --no-isolate), and emits a machine-readable result envelope

Use when the user asks for parallel team-style execution of multiple features in one project — orchestrates a team lead + N dev workers, one feature per worktree, each gated on x-qa E2E tests, with blocker escalation to human via SendMessage. Hard requires `plugin.omc` (TeamCreate/SendMessage primitives) and `.x-skills/x-qa/profile.json` (E2E gate).

Use when the user wants to evaluate x-skill alignment and improve a skill based on real session usage — searches Claude Code session history automatically

Use when user asks for non-Claude model dispatch (GPT-5, Gemini, Codex, o3) or invokes OMO agents (oracle, explore, librarian, multimodal-looker) — bridges Claude Code to OpenCode CLI, handles agent catalog, model routing flags, and prompt-block construction

Use BEFORE implementation when AI has produced a plan, spec, design doc, PRD, or code-bearing proposal and you want a senior-engineer architect-review pass — walks the user through the decisions, tradeoffs, assumptions, blind spots, shape mismatches, and future-debt AI silently embedded. Surfaces "what AI did, what it picked over alternatives, what it took on, and what gets harder later" one item at a time with confirm / modify / reject / skip gates. Hard-blocks code-level details so the human stays at architectural direction.

Use when the user wants a complex input (file, function, directory, PRD, plan, spec, URL, pasted prose, or vague feature name) explained step by step in a comprehension-gated walkthrough — produces a persistent .x-guide/<slug>/GUIDE.md with full TOC and walks the user one part at a time, supports resume across sessions

Use when a long-running skill needs to check "am I done?" — runs the canonical completion cascade with mandatory fallback to prevent silent success claims

Use when the user wants to vendor or track an upstream GitHub repo as a research reference inside the current project — adds, updates, lists, or removes `research/<owner>/<repo>` git submodules pinned to the latest stable release (not main/HEAD). Invoked for upstream code reference, dependency mirroring, or research material management.

Use when the user asks to build, implement, fix, or execute a plan — detects context (existing plan, new feature, bug, quick task, visual input) and routes through brainstorming, planning, debugging, or execution workflows

Use when the user wants to apply a visual design system to a project, references a specific brand's style (Linear-like, Stripe-like, Claude-like), asks for a DESIGN.md, or describes aesthetic intent (warm editorial, dark minimal, stark futuristic) for AI UI generation

Direct Google Gemini bridge via the Antigravity (agy) CLI — uses Google Ultra subscription (no API key), opt-in Google Search grounding (via `--grounded`), and gemini-3.x models without the OpenCode layer

Use when the user asks to research, investigate, look up, or understand something — orchestrates MCP servers (perplexity/exa/deepwiki/context7), agy-agent, and OMO agents (explore/librarian/oracle/multimodal-looker) with optional Max Mode for parallel multi-lane synthesis

Use when the user reports a bug, error, test failure, or unexpected behavior — routes through investigation, hypothesis testing, and verified fix with structured evidence collection

Implements a use case's backend: FastAPI router, Pydantic request/response schemas, service/domain layer, and SQLAlchemy models/queries. Use when the user asks to "implement the backend for UC-xxx", "build the API endpoint", "add a FastAPI route", "write the service layer", or mentions FastAPI implementation, Pydantic schemas, or SQLAlchemy queries for a specific use case.

Writes pytest unit and integration tests for a use case's backend, against an ephemeral Postgres container, and updates the use-case-to-test traceability matrix. Use when the user asks to "write tests for UC-xxx", "add pytest coverage", "test the backend", or mentions unit tests, integration tests, or pytest for a specific use case.

Implements a use case's frontend: a React view, form, or grid wired to the backend API, covering the main flow and every alternative/failure flow. Use when the user asks to "implement the frontend for UC-xxx", "build the React view", "wire up the form", "add the page for", or mentions React implementation for a specific use case.