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Found 1,203 Skills
Add Opik tracing to an existing codebase. Detects language (Python/TypeScript), identifies LLM frameworks, adds appropriate decorators and integrations, marks entrypoints, and wires up environment config. Use for "instrument my code", "add opik tracing", "add observability", or "trace my agent".
Yoast SEO platform help — the most widely used WordPress SEO plugin (13M+ installs) with a Shopify app. Covers content analysis, readability scoring, focus keyphrase optimization, schema/structured data output, redirect manager, internal linking suggestions, AI-generated meta descriptions, llms.txt for AI search, REST API for headless WordPress, and WooCommerce product SEO. Use when Yoast readability or SEO score won't turn green, schema markup isn't showing in Google Search Console, your site slowed down after installing Yoast, you need to set Yoast fields via REST API for headless publishing, Yoast update caused a critical error, or you want to configure Yoast for Shopify. Do NOT use for general SEO strategy without Yoast context (use /seo-audit or /sales-semrush).
Turn a long video into N viral-ready short clips with a single managed API call. Wraps muapi.ai's `/ai-clipping` endpoint, which handles transcription, highlight ranking through a virality framework (hook / emotional peak / opinion bomb / revelation / conflict / quotable / story peak / practical value), overlap dedupe, and vertical face-tracking auto-crop server-side. No local Whisper, no local LLM, no GPU.
Generate professional company tear sheets using S&P Capital IQ data via the Kensho LLM-ready API MCP server. Use this skill whenever the user asks for a tear sheet, company one-pager, company profile, fact sheet, company snapshot, or company overview document — especially when they mention a specific company name or ticker. Also trigger when users ask for equity research summaries, M&A company profiles, corporate development target profiles, sales/BD meeting prep documents, or any concise single-company financial summary. This skill supports four audience types: equity research, investment banking/M&A, corporate development, and sales/business development. If the user doesn't specify an audience, ask. Works for both public and private companies.
Package and build custom AI models with Cog for deployment on Replicate. Use when creating a cog.yaml or predict.py, defining model inputs and outputs, loading model weights at setup time, building Docker images for ML models, serving locally with cog serve or cog predict, or porting a HuggingFace, GitHub, or ComfyUI model to run on Replicate. Trigger on phrases like "build a model", "package a model", "create a Cog model", "wrap a model", "containerize an AI model", "predict.py", "cog.yaml", "BasePredictor", or "Cog container", and when referencing cog.run, github.com/replicate/cog, or github.com/replicate/cog-examples. Covers GPU and CUDA setup, pget for fast weight downloads, async predictors with continuous batching, streaming outputs, and cold-boot optimization for image, video, audio, and LLM models. For pushing built models to Replicate, see publish-models. For running existing models, see run-models.
Retrieval-Augmented Generation (RAG) system design patterns, chunking strategies, embedding models, retrieval techniques, and context assembly. Use when designing RAG pipelines, improving retrieval quality, or building knowledge-grounded LLM applications.
Methodology for effective AI-assisted software development. Use when helping users build software with AI coding assistants, debugging AI-generated code, planning features for AI implementation, managing version control in AI workflows, or when users mention "vibe coding," Cursor, Windsurf, or similar AI coding tools. Provides strategies for planning, testing, debugging, and iterating on code written with LLM assistance.
Automated sitemap generation for all locale URLs, robots.txt configuration, and llms.txt for AI crawler optimization. Use when setting up sitemap.xml, configuring crawling rules, or improving discoverability for search engines and AI systems.
Build AI-native products with agency-control tradeoffs, calibration loops, and eval strategies. Use when building AI agents, LLM features, or products where AI handles user tasks autonomously. Part of the Modern Product Operating Model collection.
Omniscient APEX Ecosystem development skill. Triggers: apex code, omnihub development, tradeline build, aspiral feature, apex bug, fix apex, apex architecture, omnidash component, triforce guardian, man mode, apex security, apex test, armageddon test, apex deploy, apex optimize, semantic translation, web2 web3 bridge. Produces: zero-drift, first-pass success code for APEX OmniHub, TradeLine 24/7, aSpiral, and all connected applications. Compatible with all LLMs.
Read GitHub repos the RIGHT way - via gitmcp.io instead of raw scraping. Why this beats web search: (1) Semantic search across docs, not just keyword matching, (2) Smart code navigation with accurate file structure - zero hallucinations on repo layout, (3) Proper markdown output optimized for LLMs, not raw HTML/JSON garbage, (4) Aggregates README + /docs + code in one clean interface, (5) Respects rate limits and robots.txt. Stop pasting raw GitHub URLs - use this instead.
Pre-ship audit checklist for Ethereum dApps built with Scaffold-ETH 2. Give this to a separate reviewer agent (or fresh context) AFTER the build is complete. Covers only the bugs AI agents actually ship — validated by baseline testing against stock LLMs.