Total 51,453 skills
Showing 12 of 51453 skills
Execute ES|QL (Elasticsearch Query Language) queries, use when the user wants to query Elasticsearch data, analyze logs, aggregate metrics, explore data, or create charts and dashboards from ES|QL results.
XState Store adapter for json-render's StateStore interface. Use when integrating json-render with @xstate/store for state management via @json-render/xstate.
Post-implementation reality check. Run after tests pass, before declaring done. Use when completing a feature, bug fix, refactor, or integration — or when asked to verify, sanity check, or confirm something actually works.
When the user wants to submit a product to directories, launch platforms, curated lists, or app stores. Reads product-marketing-context.md when present and generates ready-to-paste submission content per platform. Also use when the user mentions "directory submission," "get listed," "app store listing," "submit to directories," "curated list," "best tools list," "Taaft," "Product Hunt," "directory ads," "newsletter feature," "directory campaign," "product info for directory," "tailor description per platform," "Shopify App Store," "Chrome Web Store," "submit to directory," "launch on Product Hunt," "navigation site," or "product directory."
Strategic planning with optional interview workflow
test.
Web performance measurement and debugging toolkit. Use when the user asks about web performance, wants to audit a page, or says "analyze performance", "debug lcp", "check ttfb", "measure core web vitals", "audit images", or similar.
Collaborative problem-solving protocols: write technical specifications (spec, or alspec), create implementation plans (plan, or alplan), or use Align-and-Do Protocol (AAD). Also generates PR/MR descriptions (aldescription).
AI e-commerce customer service assistant that supports order query, product recommendation, and ticket processing. It can use Playwright MCP to automatically operate the e-commerce backend to query real order status.
Scrape web pages using Scrapling with anti-bot bypass (like Cloudflare Turnstile), stealth headless browsing, spiders framework, adaptive scraping, and JavaScript rendering. Use when asked to scrape, crawl, or extract data from websites; web_fetch fails; the site has anti-bot protections; write Python code to scrape/crawl; or write spiders.
This skill should be used when the user asks to "remove AI writing patterns", "humanize this text", "make this sound more natural", "remove AI-generated traces", "fix robotic writing", or needs to eliminate AI writing patterns from prose. Supports both English and Chinese text. Based on Wikipedia's "Signs of AI writing" guide, detects and fixes inflated symbolism, promotional language, superficial -ing analyses, vague attributions, AI vocabulary, negative parallelisms, and excessive conjunctive phrases.
Use ONLY when creating NEW registrable components in ML projects that require Factory/Registry patterns. ✅ USE when: - Creating a new Dataset class (needs @register_dataset) - Creating a new Model class (needs @register_model) - Creating a new module directory with __init__.py factory - Initializing a new ML project structure from scratch - Adding new component types (Augmentation, CollateFunction, Metrics) ❌ DO NOT USE when: - Modifying existing functions or methods - Fixing bugs in existing code - Adding helper functions or utilities - Refactoring without adding new registrable components - Simple code changes to a single file - Modifying configuration files - Reading or understanding existing code Key indicator: Does the task require @register_* decorator or Factory pattern? If no, skip this skill.