powershell-windows
PowerShell Windows patterns. Critical pitfalls, operator syntax, error handling.
PowerShell Windows patterns. Critical pitfalls, operator syntax, error handling.
Bash/Linux terminal patterns. Critical commands, piping, error handling, scripting. Use when working on macOS or Linux systems.
Browser action engine. Provides up-to-date action manuals for the modern web — operate any website instantly, one tab or dozens, concurrently.
Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
Generate and verify web scraper scripts using Actionbook's verified selectors. Auto-validates generated scripts and fixes errors.
Run dbt CLI commands (compile, ls, test, run, etc.) in the spellbook repo. Use when the user asks to compile, list, test, or run dbt models, or when you need to validate SQL by compiling a model.
GROWI main application (apps/app) specific commands and scripts. Auto-invoked when working in apps/app.
Execute long-running, multi-session tasks autonomously using Claude Code headless mode or in-session hook-based loops. Supports structured task decomposition (for complex projects) and lightweight Ralph-style iteration (for TDD, bug fixing, refactoring). Use this skill whenever the user says "autonomous", "long-running task", "multi-session", "run this in the background", "keep working on this", "batch process", "iterate until done", "ralph loop", or wants any task that requires sustained, unattended execution.
Modal Labs (modal.com) — run Python on serverless containers with GPUs, batch jobs, and autoscaling. Precision wrapper to avoid confusion with UI “modal dialogs”.
Enforces structured, highly documented storage for all code and data projects. Auto-activates for: machine learning scripts, data processing, code creation, script modification. Ensures clean directories, comprehensive comments, documentation files (README, data dictionaries, process descriptions, change logs).
Patterns for parallel subagent execution using Task tool with run_in_background. Use when coordinating multiple independent tasks, spawning dynamic subagents, or implementing features that can be parallelized.
Use when writing or running Nushell commands, scripts, or pipelines - via the Nushell MCP server (mcp__nushell__evaluate), via Bash (nu -c), or in .nu script files. Also use when working with structured data (JSON, YAML, TOML, CSV, Parquet, SQLite), doing ad-hoc data analysis or exploration, or when the user's shell is Nushell.
Run an agent loop until an exit condition is met. Use when the user says "loop", "babysit", "keep trying until", "check every X", "watch", or wants iterative autonomous execution.
Execute code and manage compute on Databricks. Use this skill when the user mentions: "run code", "execute", "run on databricks", "serverless", "no cluster", "run python", "run scala", "run sql", "run R", "run file", "push and run", "notebook run", "batch script", "model training", "run script on cluster", "create cluster", "new cluster", "resize cluster", "modify cluster", "delete cluster", "terminate cluster", "create warehouse", "new warehouse", "resize warehouse", "delete warehouse", "node types", "runtime versions", "DBR versions", "spin up compute", "provision cluster".
Detect and configure a conda-compatible tool, create the CausalPy environment, and run commands inside it. Use before any task that requires Python execution.
Delegate coding tasks to Codex, Claude Code, or Pi agents via background host sessions. Use when: (1) building or creating new features or apps, (2) reviewing PRs (spawn in temp dir), (3) refactoring large codebases, (4) iterative coding that needs file exploration. NOT for: simple one-liner fixes (just edit), reading code (use read tool), thread-bound ACP harness requests in chat (for example spawn or run Codex or Claude Code in a Discord thread; use sessions_spawn with runtime:"acp"), or any work in ~/clawd workspace (never spawn agents here). Requires OpenClaw host tools with exec_command plus write_stdin.
Convert an existing codebase in the current working directory into a ShinkaEvolve task directory by snapshotting the relevant code, adding evolve blocks, and generating `evaluate.py` plus Shinka runner/config files. Use when the user wants to optimize existing code with Shinka instead of creating a brand-new task from a natural-language description.
Run existing ShinkaEvolve tasks with the `shinka_run` CLI from a task directory (`evaluate.py` + `initial.<ext>`). Use when an agent needs to launch async evolution runs quickly with required `--results_dir`, generation count, and strict namespaced keyword overrides.
Create ShinkaEvolve task scaffolds from a target directory and task description, producing `evaluate.py` and `initial.<ext>` (multi-language). Use when asked to set up new ShinkaEvolve tasks, evaluation harnesses, or baseline programs for ShinkaEvolve.