Results for “research”

Search YouTube videos, channels, and trends through the AISA YouTube SERP client. Use when: the user needs YouTube search, trend discovery, channel research, or SERP analysis.

Generates full long-form content: whitepapers, eBooks, research reports, and pillar pages. Takes a content brief and produces 2000-5000 word drafts with sections, data points, and CTAs.

Develops milestone-based project descriptions for Research, Prototype, and follow-on production Other Transactions, including objectives, phases, go/no-go structures, transition planning, and cost-analysis handoffs.

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.

Retrieve deterministic search results, metadata, and full-document Markdown from arXiv, PubMed/PMC, and US policy corpora with daily freshness checks.

Extracts structured product listings from Amazon, including titles, ASINs, prices, ratings, and specifications, using the BrowserAct API.

Search the web and extract content from URLs using Exa, with support for academic and scientific sources.

Search the web and extract content from URLs using Tavily and Exa APIs via the inference.sh CLI.

Optimize AI agents through automated evolution cycles using LLM-driven mutation of prompts, skills, and memory against measurable benchmarks.

Provides expert guidance for fine-tuning LLMs with Axolotl, covering YAML configs, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, and multimodal support.

Use RWKV, a linear-time RNN-Transformer hybrid, for efficient long-context inference and training with constant memory usage.

Train, fine-tune, and deploy LLMs using LitGPT's clean implementations of 20+ architectures like Llama, Gemma, and Phi.

Deploy Meta's LlamaGuard moderation model to filter LLM inputs and outputs across 6 safety categories using HuggingFace, vLLM, or FastAPI.

Fast tokenization for NLP using Rust-based tokenizers supporting BPE, WordPiece, and Unigram algorithms, with training, alignment tracking, and padding/truncation.

Design surveys that collect reliable, unbiased quantitative data to validate hypotheses and measure user attitudes at scale.

Design click and first-click tests to evaluate navigation clarity and information findability in user interfaces.

Guides authorized RF/SDR security research for signal identification, demodulation analysis, and replay feasibility studies in shielded lab environments.

Performs a comprehensive App Store Optimization health audit, scoring listing factors and producing a prioritized action plan.

Performs neural web, code, company, and people searches through the Exa MCP server, with guidance on tool usage and parameters.

Creates and maintains minimal, high-signal AGENTS.md files for AI coding agents, following research-backed best practices for concise agent documentation.

Evidence-based health research using tiered trusted sources with GRADE-inspired evidence ratings. Integrates Apple Health data for personalized context. Use when user asks health, nutrition, exercise, sleep, or wellness questions.

Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X/Twitter within a configurable recent window (default 30 days).

Diverga Memory System v7.0 - Context-persistent research support with checkpoint auto-trigger and cross-session continuity. Triggers: memory, remember, context, recall, checkpoint, decision, persist, 기억, 맥락, 세션, 체크포인트

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 `youtube`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. YouTube SERP Scout for agents. Search top-ranking videos, channels, and trends for content research and competitor tracking. Use when: the user needs YouTube search, trend discovery, channel research, or SERP analysis.

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 `scholar-search`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Search academic papers and scholarly articles via AIsa Scholar endpoint. Supports year range filtering for targeted research. Use when: the user needs web search, research, source discovery, or content extraction.

Plan content strategies that drive traffic, build authority, and generate leads by classifying topics as searchable or shareable.

Extracts the user's true intent through one-question-at-a-time interviews, surfacing hidden assumptions before any plan or code is written.

Generate SEO-optimized pages at scale using templates and data to capture long-tail search traffic.

Creates and maintains minimal, high-signal AGENTS.md files for AI coding agents, enforcing research-backed best practices for concise agent documentation.

Extract full article contents from WeChat using the BrowserAct API, with keyword search and date filtering.

Access comprehensive LaTeX templates, formatting requirements, and submission guidelines for major scientific publication venues, academic conferences, research posters, and grant proposals.

Enables fast similarity search and clustering of dense vectors using FAISS, supporting billions of vectors, GPU acceleration, and various index types.

Track ML experiments with open-source run logging, local or self-hosted dashboards, and media visualization using SwanLab.

Build teams of autonomous AI agents that collaborate to solve complex tasks using role-based delegation, memory, and sequential or hierarchical execution.

Connects LLMs with user data for RAG applications, document Q&A, and knowledge retrieval using 300+ data connectors and vector indices.