Results for “ai-research”

Use when a complete research workflow — its instructions, skills, data boundaries, and tool connections — must be assessed for portability across AI agents or environments, so each component is explicitly mapped before migration rather than assumed to transfer.

Extract clean, readable content from one or more URLs using Tavily Extract via AIsa API. Useful for reading full articles without visiting the page. Use when: the user needs web search, research, source discovery, or content extraction.

Write scientific manuscripts in full paragraphs using IMRAD structure, with citations (APA/AMA/Vancouver), figures/tables, and reporting guidelines (CONSORT/STROBE/PRISMA) for research papers and journal submissions.

Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification workflows.

Advanced web search via Tavily through AIsa API. Supports search depth, topic filtering (general/news/finance), time ranges, domain inclusion/exclusion, and LLM-generated answers. Use when: the user needs web search, research, source discovery, or content extraction.

ByteDance's open-source super agent harness — spawns parallel sub-agents, Docker sandbox execution, persistent long-term memory, modular skills (research/report/slides). Built on LangChain + LangGraph. Triggers on: 'deerflow', 'deer-flow', 'bytedance agent', 'super agent harness', 'LangGraph agent orchestration', 'multi-hour agent tasks', 'spawn sub-agents', 'agent sandbox docker', 'persistent agent memory', 'agent skills system', 'AI research orchestrator', 'long-running agent tasks', 'agent with memory', 'langgraph orchestrator', 'IM channel agent integration'.

Benchmark-relative quality gate. Scores the draft against the research dossier's beat spec (depth, consensus coverage, evidence) plus AI-tell and voice signals, runs an adversarial read armed with the SERP benchmark, and emits the verdict that gates the pipeline.

Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. For systems venues (OSDI, NSDI, ASPLOS, SOSP), use systems-paper-writing instead.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `trend-forecast`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Multi-signal trend forecasting for autonomous agents. Combines prediction market odds, Twitter/X social sentiment, news velocity, and stock market data into a unified trend analysis with confidence scoring. Powered by AIsa — one API key, five data streams. Use when: the user needs X/Twitter research, monitoring, posting, or engagement workflows.

This skill should be used when the user asks to "find skills in the wild", "assimilate popular workflows", "discover SKILL.md files in repos", "research external skills", "find workflow patterns", "survey the skill landscape", "what skills exist out there", or wants to investigate public repositories for extractable processes, babysitter plugins, and reusable procedural insights. Searches GitHub for SKILL.md files, classifies repos by archetype, and maintains structured research under docs/reference-repos/.

Query real-time and historical cryptocurrency market data via CoinGecko through AIsa — simple prices, coin details, historical charts, OHLC candles, token prices by contract address, market-cap rankings, exchange data and tickers, categories, trending searches, and crypto news. Use when you need crypto market research, price tracking, token lookup, portfolio analysis, or market-cap screening. Use when: the user needs market data, stock analysis, dividend research, or read-only financial data workflows.

Requires python3, bash, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `last30days`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Research the last 30 days across Reddit, X, YouTube, TikTok, Instagram, Hacker News, Polymarket, GitHub, and grounded web search. Returns a ranked, clustered brief with citations. Use when the task needs recent social evidence, competitor comparisons, launch reactions, trend scans, or person/company profiles.

Forecast any univariate time series (sales, sensors, energy, vitals, weather) zero-shot using Google's TimesFM foundation model, with point forecasts and prediction intervals from CSV, DataFrame, or array inputs.

Search X/Twitter profiles, tweets, trends, lists, communities, and Spaces through the AISA relay, then publish approved posts with OAuth. Use when: the user asks for Twitter/X research, monitoring, or posting without sharing passwords. Supports read APIs, authorization links, and media-aware posting.

Evaluate scientific claims and evidence quality by assessing experimental design, identifying biases and confounders, and applying evidence grading frameworks like GRADE and Cochrane Risk of Bias.

Artistic, research-grounded UI enhancement for making an existing page feel intentional, spacious, and human-crafted. Use when "make this page nicer/polished/premium/editorial", less crowded, better laid out, typography, or visual hierarchy. Flows/AI-templated UX → enhance-web-ux. Layout contract → audit-responsive.

Search X/Twitter profiles, tweets, trends, and approved engagement actions through the AISA relay. Use when: the user asks for Twitter/X research, posting, likes, follows, or related workflows without sharing passwords. Supports read APIs, OAuth-gated posting, and follow or like operations.

Complete SEO + GEO (Generative Engine Optimization) system for SaaS companies wanting to rank on both Google and AI search engines (ChatGPT, Perplexity, Gemini, Claude). Use this skill whenever the user asks about SEO strategy, keyword research, content planning, writing SEO-optimized articles, auditing their search performance, creating a content calendar, analyzing competitors, or optimizing for AI search visibility. Trigger on: "seo", "keyword research", "content calendar", "rank on google", "search traffic", "write an article", "blog post", "serp", "backlinks", "competitor analysis", "content cluster", "seo audit", "geo optimization", "ai search", "search console", "organic traffic", "content strategy", "publish article", "seo setup", "ranking", "impressions", "ctr", "meta description", "schema markup", "faq schema". Also trigger when a user wants to set up their SaaS blog SEO from scratch, analyze their current rankings, or create a publishing workflow.

Use this skill when a user needs KOL or influencer research, creator email lookup, similar-creator discovery, outreach-list building, influencer prospecting, or a contact table from TikTok, Instagram, or YouTube profile URLs. It uses AIsa's WaveInflu APIs to find verified creator emails, match similar YouTube or TikTok creators, enrich each recommended profile with contact emails, and return an outreach-ready Markdown table without inventing missing data. Use when: the user needs YouTube search, trend discovery, channel research, or SERP analysis.

Generate professional clinical decision support documents for pharmaceutical and clinical research, including biomarker-stratified cohort analyses and evidence-based treatment recommendation reports with GRADE grading, statistical analysis, and publication-ready LaTeX/PDF output.

Mine LITCOIN — a proof-of-comprehension and proof-of-research cryptocurrency on Base. Use when the user wants to mine crypto with AI, earn tokens through reading comprehension or solving optimization problems, stake LITCOIN, open vaults, mint LITCREDIT, manage mining guilds, deploy autonomous agents, or interact with the LITCOIN DeFi protocol.

Layer 1a of the keyword research pipeline. Generates seed keywords (broad niche terms) and modifiers (best, how-to, vs, calculator, etc.) from brand-config so the keyword multiplier has a real foundation to expand from. Replaces the "AI gives you generic keywords" problem with the structured 10-second hero prompt.

You are an expert in AG2 (formerly AutoGen), the open-source multi-agent conversation framework. You help developers build systems where multiple AI agents collaborate through structured conversations — with tool use, human-in-the-loop, code execution, group chat orchestration, and nested conversations — for complex tasks like software development, research, and data analysis.

Analyze read-only dividend metrics for stocks via AIsa API. Provides yield, payout ratio, growth CAGR, safety score, income rating, and Dividend Aristocrat/King status without placing trades, making purchases, or managing brokerage accounts. Use when: the user needs market data, stock analysis, dividend research, or read-only financial data workflows.

Multi-signal trend forecasting for autonomous agents. Combines prediction market odds, Twitter/X social sentiment, news velocity, and stock market data into a unified trend analysis with confidence scoring. Powered by AIsa — one API key, five data streams. Use when: the user needs X/Twitter research, monitoring, posting, or engagement workflows.

This skill should be used when the user asks about crypto prices, market data, K-line charts, funding rates, open interest, long/short ratios, whale orders, liquidation data, crypto news, newsflash, Twitter crypto tweets, trending coins, airdrops, drop radar, airdrop research, project analysis, exchange listings, stock quotes, treasury holdings, or any crypto market query. Also use when user asks about configuring or checking AiCoin API key. Use when user says: 'BTC price', 'check price', 'show K-line', 'funding rate', 'open interest', 'whale orders', 'long/short ratio', 'crypto news', 'newsflash', 'ETF', '监管', '政策', 'trending coins', 'airdrop', 'drop radar', '查行情', '看价格', '大饼多少钱', 'K线', '资金费率', '多空比', '鲸鱼单', '新闻', '快讯', '新闻快讯', '热门币', '空投', '空投项目', '空投机会', '空投研报', '项目分析', '项目详情', '上了哪些交易所', '推特', 'Twitter', 'liquidation map', '配置AiCoin key', 'AiCoin API key', 'AiCoin key安全吗'. Covers 200+ exchanges with real-time data. MUST run node scripts to fetch real data. NEVER generate fake prices or hallucinate market

Layer 4 of the keyword research pipeline. Spawns a "skeptical SEO" adversarial sub-agent to argue against every survivor of Layers 1-3. Catches mechanical-classifier blind spots — wrong SERP intent, hidden link-graph gauntlets, AIO trajectory shifts, vanity-rank metrics. Same pattern as quality-check's adversarial draft read, applied to keyword selection.

Systematic strategic planning framework for philosophy and interdisciplinary academic papers targeting preprint platforms (PhilArchive, arXiv, PhilSci-Archive). Use when users want to: (1) plan a paper on a specific topic, (2) identify research gaps and assess originality, (3) develop optimized paper outlines, (4) prepare for preprint submission, or (5) understand platform requirements and writing standards. Triggered by phrases like 'plan a paper on,' 'help me design a paper about,' 'identify research gaps in,' 'is this idea original,' or when users need structured research planning. The skill guides through three phases: Platform Analysis (identifying target venue and studying sample papers), Theoretical Framework (AI-driven literature search and gap identification), and Outline Optimization (structured design with reviewer-perspective self-assessment). Each phase includes quality evaluation standards and validation checkpoints. Output: optimized detailed outline ready for systematic writing (use with acade

Layer 1b of the keyword research pipeline. Finds keyword opportunities by comparing the brand's blog against competitors AND by expanding seeds + modifiers via Semrush (phrase_fullsearch / phrase_related). Auto-discovers competitors via domain_organic_organic when none are provided, derives the keyword gap via domain_domains, tags every row with `gap_mode`, and outputs a candidate-keyword CSV ready for downstream BID/AIO vetting.

Use when someone asks what is true, false, misleading, unsupported, unknown, or genuinely complicated in a persuasive message, article, pitch, advertisement, policy claim, or viral post. Analyze propaganda, spin, selective framing, urgency, social proof, deceptive marketing, and AI-generated persuasion by tracing claims to evidence and separating literal truth from implied conclusions. Do not use to read deception from demeanor, adjudicate intent, or replace broad domain research.

Browse, group, relate, and selectively install the jeo-skills catalog through the lightweight `jeo-skill` CLI. Use when the user wants skills organized by web, infrastructure, game, creative media, CLI tools, AI/agents, engineering, research, business, or utilities; needs a frontend/backend/game-audio/game-VFX subcategory; wants overlapping skills connected instead of duplicated; or wants a category, bundle, or named skills installed without copying the full repository.

Legacy-project style inheritance skill. Use when the user types /inherit-legacy-style, or when onboarding an AI coding agent onto a hand-written legacy project and you need to prevent "style drift" (the model imposing its pretrained mainstream idioms onto the project). Language- and framework-agnostic — it aligns meta-architecture only, not syntax. Once run, it becomes a behavioral constraint on all subsequent coding tasks. Do NOT use for pure research or one-off questions unrelated to code-style alignment.

Lazyweb is the design-evidence skill for AI coding agents. Use it when designing, critiquing, or changing product UI — it provides real app screenshots, competitor references, best practices, quick examples, creative cross-category ideas, paywall optimization guidance, and mobile growth + monetization A/B test context. Routes to the right Lazyweb mode (design workflow, quick search, update, flowchart, or A/B test research) using MCP tools and the Lazyweb server at https://www.lazyweb.com/mcp. Use before designing any screen when you need design evidence instead of training-data vibes.

Automatically rig 3D models with UniRig (VAST-AI-Research, SIGGRAPH'25) — predict a skeleton, predict skinning weights, and merge the rig back onto the original mesh. Use when the user wants auto-rigging for .obj/.fbx/.glb/.gltf/.dae/.vrm assets, a skeleton or skin weights for a character or creature, a UniRig environment prepared on a CUDA machine, batch rigging of a model directory, or an honest comparison between UniRig, SkinTokens, Tripo, Mixamo, AccuRig, and Blender Rigify. Triggers on: unirig, auto rig, auto-rigging, 3D rigging, skeleton prediction, skinning weights, rig a character, armature generation, rigged glb, rigged fbx, bone weights.