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Found 56 Skills
AI-optimized web search using Tavily Search API. Use when you need comprehensive web research, current events lookup, domain-specific search, or AI-generated answer summaries. Tavily is optimized for LLM consumption with clean structured results, answer generation, and raw content extraction. Best for research tasks, news queries, fact-checking, and gathering authoritative sources.
This skill should be used when users need to search the web for information, find current content, look up news articles, search for images, or find videos. It uses DuckDuckGo's search API to return results in clean, formatted output (text, markdown, or JSON). Use for research, fact-checking, finding recent information, or gathering web resources.
USE FOR web search, research, RAG, grounding, browse, find, lookups, fact-checking, documentation, agentic AI. All-in-one, optimized for AI agents. Pre-extracted, token-budgeted web content, deep research, news, images, videos, places, custom ranking
Verify statistics from raw data with methodology checking, significance testing, claim validation, and bias detection. Use when fact-checking statistical claims, validating research findings, or auditing data analysis.
Skill for optimizing article style to remove AI flavor. Used to identify and rewrite issues such as AI traces, template tone, material-like style, translationese, empty buzzwords, excessive golden sentences, overuse of em dashes, bullet stacking, and random bolding in articles, official account drafts, self-media drafts, oral broadcast scripts, speech scripts, course scripts, and product copy; activated when users say phrases like "remove AI flavor", "eliminate AI traces", "not written by AI", "more human-written", "more natural", "less robotic", "remove template feel", "polish to official account final draft". Not applicable for fact-checking, zero-based topic planning, converting papers to official account articles, pure title generation, or pursuing AI detector pass rates.
Search the web for information using DuckDuckGo or other search engines via curl. Use when users ask questions requiring up-to-date information, research, or fact-checking.
NVIDIA's runtime safety framework for LLM applications. Features jailbreak detection, input/output validation, fact-checking, hallucination detection, PII filtering, toxicity detection. Uses Colang 2.0 DSL for programmable rails. Production-ready, runs on T4 GPU.
LLM guardrails with NeMo, Guardrails AI, and OpenAI. Input/output rails, hallucination prevention, fact-checking, toxicity detection, red-teaming patterns. Use when building LLM guardrails, safety checks, or red-team workflows.
Search for recent news and developments on a topic, organize them chronologically, and deliver a concise briefing. Use this skill when the user wants to catch up on recent events, news, or developments around a topic. Trigger on phrases like "what's new with X", "recent news about X", "any updates on X", "what happened with X lately", "catch me up on X", "news roundup for X", "what did I miss about X", "latest developments in X", or "has anything changed with X recently". Also trigger when the user mentions a time frame like "this week", "this month", "since January", or "in the last few days" combined with wanting information. Don't trigger for general research, product comparisons, or fact-checking — only when recency is the point.
General-purpose web search using DuckDuckGo and AI-synthesized search engines. Use this skill for web searches, current information, fact-checking, news, and research on any topic where live internet data is needed. Supports all languages. Three modes: fast web results, AI-synthesized answers (IAsk.ai, great for deep questions and academic research), and Monica AI synthesis. Trigger on: "search for", "look up", "find information about", "what is the latest", "search the web", "find out about", "what happened with", "current status of", "recent news", "is X still true", "查一下", "搜索", "查资料", "上网查", "検索して", "調べて", any question requiring real-time or post-training web data. Do NOT trigger for: code exploration, local file analysis, codebase-internal questions, or well-established facts fully covered by training knowledge. Note: if the `agent-reach` skill is also available, prefer `ddg-search` for pure web search tasks; prefer `agent-reach` when the task involves social platforms (Twitter, Reddit, YouTube, WeChat, Bilibili, etc.) or platform-specific APIs.
Verifies factual claims in documents using web search and official sources, then proposes corrections with user confirmation. Use when the user asks to fact-check, verify information, validate claims, check accuracy, or update outdated information in documents. Supports AI model specs, technical documentation, statistics, and general factual statements.
Three-layer verification pipeline for AI output. Extracts verifiable claims, finds supporting or contradicting sources via web search, runs adversarial review for hallucination patterns, and produces a structured verification report with source links for human review.