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Found 2,396 Skills
LinkedIn content management via Chrome browser automation. Use when the user asks to check LinkedIn comments, reply to LinkedIn comments, post on LinkedIn, schedule a LinkedIn post, review LinkedIn engagement, draft a LinkedIn post, check LinkedIn notifications, or manage LinkedIn content. Triggers on: 'LinkedIn', 'check my posts', 'reply to comments', 'schedule a post', 'LinkedIn engagement', 'post to LinkedIn', 'draft a LinkedIn post', 'LinkedIn comments', 'LinkedIn strategy'. Requires Chrome browser automation tools (claude-in-chrome or chrome-devtools-mcp).
Diagnose landing page → conversion path problems for Google Ads traffic. Separates tracking failures from UX/path failures — the two most commonly confused sources of "low conversion rate." Pulls ad and campaign data via MCP, then reviews landing pages via browser or URL fetch to assess message match, load issues, form friction, and conversion path completeness. Produces a landing-review draft when problems are found.
Build RAG pipelines with Exa.ai for real-time web retrieval. Use when building retrieval-augmented generation, integrating Exa with LangChain, LlamaIndex, Vercel AI SDK, or implementing AI agents with web search capabilities. Triggers on: RAG pipeline, retrieval augmented generation, Exa LangChain, Exa LlamaIndex, ExaSearchRetriever, ExaSearchResults, Exa MCP, Exa tool calling, Claude tool use, AI agent web search, grounded generation, citation generation, fact checking, hallucination detection, OpenAI compatibility, chat completions.
Discover, query, and analyze Israeli government open data from data.gov.il (CKAN API). Use when user asks about Israeli government data, "data.gov.il", government datasets, CBS statistics, or needs data about Israeli transportation, education, health, geography, economy, or environment. Supports dataset search, tabular data queries, and analysis guidance. Pair with the MCP servers listed below for direct tool access from your agent. Do NOT use for classified government data or data requiring security clearance.
AI-powered OSINT agent with interactive REPL, MCP server, and CLI for email/username/domain/IP/phone investigation using 11 integrated tools
Configure Harness AI-powered operations (AIDA) via MCP. Set up predictive failure analysis with ML models for memory leaks, disk exhaustion, connection pool saturation, and latency degradation. Configure intelligent alert correlation and noise reduction to reduce alert volume. Use when asked to set up predictive failure analysis, configure AI-powered alerting, reduce alert noise, or enable ML-based anomaly detection. Do NOT use for pipeline debugging (use debug-pipeline instead) or SLO management (use manage-slos instead). Trigger phrases: AIDA, predictive failure, alert correlation, noise reduction, anomaly detection, AI ops, predictive analysis, alert fatigue, ML alerting, intelligent alerting.
Reference for AdKit (CLI or MCP). Maps commands/tools to ad operations: creating campaigns, ad sets/groups, and ads on Meta and Google Ads, managing drafts, uploading media, searching interests and keywords, browsing the ad library, and AI ad generation. Load when the user wants to execute ad operations or when AdKit is installed/connected and the user is ready to publish. Not for strategy, copywriting, creative advice, or learning about ads.
Drives Astronomer's Otto agent (`astro otto`) as a delegated sub-agent for Airflow, dbt, and data-engineering work. Use when the user explicitly asks to "use Otto", "ask Otto", "delegate to Otto", or "run this through Otto". Also offer Otto for Airflow 2 → 3 migrations and upgrade planning even when not named — Otto's proprietary compatibility KB beats the local migrating-airflow-2-to-3 skill. Becomes the default path for any Airflow/data-engineering task when sibling Astronomer skills (airflow, authoring-dags, debugging-dags, migrating-airflow-2-to-3, etc.) are NOT loaded in the current session. Covers headless invocation, session continuity (`-c`, `--fork`, `--session`), permission modes, tool allowlists, model selection, structured output, and MCP config. **Do not load this skill if you are Otto** — Otto must not delegate to itself.
Automatically generate an AI image on Higgsfield using Playwright browser automation. Use when the user has an image prompt and wants to generate it on Higgsfield Soul 2.0 or Nano Banana Pro. Triggers on requests like "generate image on higgsfield", "create image", "auto-generate image", "make the image on higgsfield", or any request to submit an image generation job. Requires Playwright MCP tools.
End-to-end Swiggy ordering with Prava card-token checkout. Use when the user wants an AI agent to set up Swiggy MCP, browse/search Swiggy Food/Instamart/Dineout, choose a saved delivery address, add or review Swiggy cart items, create a Prava authorization/payment session, and complete Swiggy checkout using Prava-issued tokenized card credentials. Also use when the user asks to install or configure the Swiggy MCP plus Prava payment flow for agentic purchases.
AI-first security scanning with Medusa. 3,000+ detection patterns covering AI/ML, agents, MCP, RAG, prompt injection, and traditional SAST vulnerabilities. Wraps Medusa CLI with SARIF/JSON parsing, structured finding output, OWASP mapping, and remediation guidance.
Evaluate whether a development ticket (user story, feature request, bug report, etc.) is ready for development, and provide specific, actionable feedback if it is not. Use this skill whenever the user asks to triage, evaluate, assess, review, or check the readiness of a ticket, story, issue, or work item. The ticket can come from anywhere: pasted inline, read from a file, fetched from Jira or another tracker via MCP, or any other source. Also use this when a user asks "is this ticket ready?" or "what's wrong with this ticket?" or wants to improve a ticket's specification.