Generate images, charts, plots, and visualizations. Use when the user asks to draw, plot, chart, visualize data, or create images.

Analyze conversations to extract reusable skill patterns. Used internally by FastClaw to auto-generate skills from complex multi-step tasks.

Create new skills for FastClaw agents. Use when the user asks to create a skill, turn a workflow into a skill, or build reusable automation. Also use when discussing skill format, structure, or best practices.

Analyze data, process CSV/JSON files, compute statistics, and create data visualizations. Use when the user asks about data processing, statistics, or analysis.

Execute code in multiple programming languages. Use when the user asks to run, test, or debug code in Python, JavaScript, shell, or other languages.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

Run this BEFORE any package install (pip / npm / apt / brew / cargo / gem / go install) you would otherwise execute via the exec tool — including when the user asks for a deliverable that needs third-party libraries (PDF generation, image processing, scrapers, dashboards, charts, OCR, audio/video, …). It searches the open agent-skill ecosystem (skills.sh) for an installable skill that already does the job; only fall back to direct package install if find-skills returns no credible match. Also covers explicit "find a skill for X" / "how do I do X" / "is there a skill that can..." requests, and any time the user expresses interest in extending agent capabilities.

Anti-detect browser automation CLI & Skills for AI agents. Use when the user needs to interact with websites with bot detection, CAPTCHAs, or anti-bot blocks, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task that requires bypassing fingerprint checks.

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.

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.

Load top-performing Shinka programs into agent context using `shinka.utils.load_programs_to_df`, and emit a compact Markdown bundle for iteration planning.

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.

Iterative development with AI review. Provides RLCR (Ralph-Loop with Codex Review) for implementation planning and code review loops.

Refine an annotated implementation plan into a comment-free plan and a QA ledger while preserving the gen-plan schema.

Generate a structured implementation plan from a draft document. Validates input, checks relevance, analyzes for issues, and generates a complete plan.md with acceptance criteria.

Consult Gemini as an independent expert with deep web research. Sends a question or task to Gemini CLI and returns a research-backed response.

Session wrap-up: commit pending changes, push, write structured state for the next session to resume from. Eliminates 'glue sessions' that exist only to commit/push, and preserves debug context across sessions.

Agent Loop for pixel-perfect UI adjustments: extract a structured spec from the user's intent, apply changes one property at a time, self-verify via screenshot, and converge instead of ping-ponging. Designed for high-fidelity UI cloning and spacing/style iteration.

TRIGGER when writing, modifying, or reviewing any Rust code that involves tracing, logging, spans, events,

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes