Audits a live website for AI-engine discoverability (AEO/GEO). Crawls the site, runs 16 deterministic checks plus a 6-dimension content evaluation, and produces a scored report (A-F) with prioritized fixes. Use to get a baseline before improve-aeo-geo, or to measure progress after changes.

Verifies truthfulness, accuracy, and link integrity of content before publishing. Catches fabricated statistics, dead URLs, misattributed sources, and company claims that contradict the brand DNA.

Search the web and fetch web pages. Use when the user asks to search for information, look something up, or fetch a URL.

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.

Self-learning system that captures corrections during sessions and reminds users to run /reflect to update CLAUDE.md. Use when discussing learnings, corrections, or when the user mentions remembering something for future sessions.

Scan an iOS/macOS Xcode project for common App Store rejection patterns before submission. Use when preparing an app for App Store review, after receiving a rejection from Apple, or when auditing metadata, subscriptions, privacy manifests, entitlements, or design compliance. Integrates with the asc CLI for metadata inspection.

Redesign GitHub README homepages or create project-native pure SVG, hybrid SVG-composed PNG/WebP, and opt-in animated GIF assets. Use when a user asks to beautify, redesign, rebrand, visually upgrade, simplify, or audit a GitHub README; create only a hero, section headers, diagrams, badges, motion graphics, showcase modules, or other README assets; or turn a repository homepage into a cohesive visual story. If whole-README work versus asset-only work is unclear, ask which scope the user wants. For hero-like assets where pure SVG and generated raster material are both viable, explain the tradeoffs and confirm the implementation before creating the asset.

Design LLM applications using the LangChain framework with agents, memory, and tool integration patterns. Use when building LangChain applications, implementing AI agents, or creating complex LLM workflows.

Create learning paths for programming tools, and define what information should be researched to create learning guides. Use when user asks to learn, understand, or get started with any programming tool, library, or framework.

Provides checklist for reviewing Typer CLI command implementations. Covers structure, Annotated syntax, error handling, exit codes, display module usage, destructive action patterns, and help text conventions. Use when user asks to review/check/verify a CLI command, wants feedback on implementation, or asks if a command follows best practices.

Generate pytest tests for Typer CLI commands. Includes fixtures (temp_storage, sample_data), CliRunner patterns, confirmation handling (y/n/--force), and edge case coverage. Use when user asks to "write tests for", "test my CLI", "add test coverage", or any CLI + test request.

Provides Typer templates, handles registration, and ensures consistency. ALWAYS use this skill when adding or modifying CLI commands. Use when user requests to add/create/implement/build/write a new command (e.g., "add edit command", "create search feature") OR update/modify/change/edit an existing command.

Generate educational practice questions from lecture notes to test student understanding. Use when users request practice questions, exam preparation materials, study guides, or assessment items based on lecture content.