「search skill」の検索結果

AiZynthFinder retrosynthetic route planning (CASP) from AstraZeneca Molecular AI. Monte Carlo tree search guided by a template-based neural expansion policy recursively disconnects a target SMILES until precursors are found in a purchasable stock. Covers config.yml (v4 format), aizynthcli batch screening, the AiZynthFinder/AiZynthExpander Python API, one-step disconnections, custom stocks via smiles2stock, scorers, Retro*/breadth-first/DFPN search alternatives, and reading output.json.gz / trees.json. Use for synthesis route planning, synthesizability screening, and building-block/precursor search. For reaction barriers use neb-irc-activation-energy; for 2D reaction scheme drawing use rdkit-chemdraw-cdxml.

日本語の概要は準備中です。原文の説明を表示しています。

Programmatic PubMed access via NCBI E-utilities REST API. Covers Boolean/MeSH queries, field-tagged search, endpoints (ESearch, EFetch, ESummary, EPost, ELink), history server for batches, citation matching, systematic review strategies. Use for biomedical literature search or automated pipelines.

日本語の概要は準備中です。原文の説明を表示しています。

Implement semantic vector search for construction data. Build AI-powered search using embeddings and vector databases (Qdrant, ChromaDB) for intelligent querying of specifications, standards, and project documents.

日本語の概要は準備中です。原文の説明を表示しています。

Operate the Deep Researcher Agent repository for autonomous deep-learning experiments, execution backends, provider/tool dispatch, GPU resources, durable progress, and research-support integrations.

日本語の概要は準備中です。原文の説明を表示しています。

Use ARIS, the Auto Research in Sleep skill-based research harness, for setup, workflow routing, reviewer backend integration, state recovery, experiment operations, and repository maintenance.

日本語の概要は準備中です。原文の説明を表示しています。

Expert patterns for Algolia search implementation, indexing strategies, React InstantSearch, and relevance tuning

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.

日本語の概要は準備中です。原文の説明を表示しています。

只读检索小红书公开内容，并把账号数据、标题、封面、互动量、作者近期内容和低粉爆款整理成可追溯证据。用户要求查公开账号或笔记数据时使用；不得点赞、收藏、评论、发布、删除或导出登录凭证。 English: Read-only research for public Xiaohongshu content, collecting traceable evidence such as account data, titles, covers, engagement, recent posts, and low-follower breakout examples. Use for public account or post research; never like, save, comment, publish, delete, or export credentials.

日本語の概要は準備中です。原文の説明を表示しています。

SDT 内容生产工具箱的总入口：根据当前任务选择最合适的 sdt-* 模块，既能完成标题、开头等单一步骤，也能组织从账号研究到发布的完整流程。用户不知道该用哪个 SDT Skill，或希望一站式完成内容生产时使用。 English: Main entry point for the SDT content-production toolkit. Use when the user is unsure which sdt-* skill to choose, wants a single step such as a title or hook, or wants an end-to-end workflow from account research to publishing.

日本語の概要は準備中です。原文の説明を表示しています。

Conducts Privacy Impact Assessment for health data processing under GDPR Article 9, HIPAA, and sector-specific health privacy regulations. Covers special category data safeguards, clinical research data, patient portals, health wearables, genetic data, and cross-border health data transfers. Keywords: health data PIA, DPIA, Article 9, HIPAA, special category data, clinical research, patient privacy, genetic data.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.

日本語の概要は準備中です。原文の説明を表示しています。

Researches an open-ended question — options, possible solutions, prior art, trade-offs, or how something works — and produces a durable, evidence-backed, adversarially-validated report that recommends an option without committing the team to any artifact. Use when you want to research approaches, weigh options, survey prior art or the state of the art, or understand how something works before committing to a direction. Does not diagnose a bug, failure, or root cause — use investigate. Does not specify a feature — use plan-a-feature. Does not create or update a coding standard — use coding-standard. Does not compare two concrete artifacts for gaps — use gap-analysis. Does not assess an existing module's architecture — use architectural-analysis. Does not capture feedback on Han's own skills — use han-feedback.

日本語の概要は準備中です。原文の説明を表示しています。

Interact with Outlook email — read inbox, send emails, search messages, reply/forward, manage folders, download attachments. Use this skill whenever the user mentions email, Outlook, inbox, mail, send email, check email, unread messages, email search, attachments, reply to email, forward email, 邮件, 收件箱, or wants to read, send, search, reply to, forward, or manage emails.

日本語の概要は準備中です。原文の説明を表示しています。

Interact with Microsoft Teams — send and read messages, search conversations, look up people, check calendar, get meeting transcripts, and manage chats. Use this skill whenever the user mentions Teams, MS Teams, Microsoft Teams, wants to send a message, read chat history, search conversations, look up a colleague, check their calendar, find meeting recordings or transcripts, see direct reports or manager, or do anything involving Teams communication. Also trigger when the user asks about scheduling, org chart, people search, or wants to message someone.

日本語の概要は準備中です。原文の説明を表示しています。

想法群聊室 — 调研员角色。被 idea-team 主编排器调用，或用户单独说"调研一下 X"、"X 的现状/竞品/数据"、"找 2026 数据"、"事实底"时触发。**用 WebSearch 拉真实 2026 数据、列竞品、引来源——只给事实，不评判，不建议**。Do NOT use when 用户要评价想法好坏（那是反方）、或要跨界启示（那是类比者）、或已有 PRD 在跑（不需要这种调研）。插件内 skill 会由 `idea-coach` namespace 路由；catalog 用户直接按 skill 名调用。

日本語の概要は準備中です。原文の説明を表示しています。

This skill should be used when analyzing recent market-moving news events and their impact on equity markets and commodities. Use this skill when the user requests analysis of major financial news from the past 10 days, wants to understand market reactions to monetary policy decisions (FOMC, ECB, BOJ), needs assessment of geopolitical events' impact on commodities, or requires comprehensive review of earnings announcements from mega-cap stocks. The skill automatically collects news using WebSearch/WebFetch tools and produces impact-ranked analysis reports. All analysis thinking and output are conducted in English.

日本語の概要は準備中です。原文の説明を表示しています。

Applies the reasoning, architectural principles, and AI philosophy of Christopher Manning (natural language processing expert, Stanford University, director of Stanford AI Lab). Use this skill whenever you are discussing natural language processing, LLM architecture, AI research strategy, cognitive science, or the evolution of machine learning. Trigger this skill for questions about AGI timelines, academic vs. industry research trade-offs, linguistic structure in neural networks, modularity in AI design, or evaluating true intelligence versus mere memorization. Channel his pragmatic focus on domain science, adaptability, and competing on ideas rather than raw compute.

日本語の概要は準備中です。原文の説明を表示しています。

Applies the reasoning of David Silver, lead researcher on AlphaGo and AlphaZero at DeepMind, to problems of AI design, reinforcement learning, and open-ended discovery. Use this skill whenever you are designing AI systems, evaluating learning algorithms, balancing exploration vs. exploitation, choosing research problems, or discussing how to break past human performance ceilings. Reach for this whenever the user asks about self-play, Monte-Carlo Tree Search, tabula rasa learning, AGI, or moving from human-curated data to autonomous experience. It helps shift the focus from hardcoding human knowledge to building systems that learn for themselves.

日本語の概要は準備中です。原文の説明を表示しています。

Applies the reasoning style of Ilya Sutskever (deep learning pioneer, co-founder of OpenAI and Safe Superintelligence Inc.) to problems involving AI architecture, scaling laws, alignment, and research strategy. Reach for this skill whenever discussing machine learning paradigms, the limits of compute and data, AGI timelines, superintelligence safety, or deciding between hardcoding vs. learning. Trigger this skill for questions about next-word prediction, reinforcement learning efficiency, generalization gaps, and transitioning from brute-force scaling to fundamental research, even if the user doesn't explicitly name him.

日本語の概要は準備中です。原文の説明を表示しています。

Applies the engineering and research philosophies of Jeff Dean, Chief Scientist at Google DeepMind and Google Research. Reach for this skill whenever you are designing large-scale distributed systems, optimizing latency and energy efficiency, or making architectural decisions about machine learning infrastructure. It should trigger automatically for topics involving hardware-ML co-design, model distillation, sparse activation, massively multi-task models, or scaling systems by 5x to 10x. Use this skill to evaluate system bottlenecks, transition from specialized to unified models, and optimize experimental velocity. Apply his mental models to avoid premature 100x scaling and to treat AI models as reasoning engines rather than memorization databases.

日本語の概要は準備中です。原文の説明を表示しています。

Amazon Elasticsearch integration. Manage data, records, and automate workflows. Use when the user wants to interact with Amazon Elasticsearch data.

日本語の概要は準備中です。原文の説明を表示しています。

Algolia Search integration. Manage Indexs, Records, Rules, Tasks, Clusters, Users. Use when the user wants to interact with Algolia Search data.

日本語の概要は準備中です。原文の説明を表示しています。

AddSearch integration. Manage data, records, and automate workflows. Use when the user wants to interact with AddSearch data.

日本語の概要は準備中です。原文の説明を表示しています。

Analyze Chinese notes, articles, manuscripts, and digital card-box material with FIRE 2.0: Full-D numbering, Index keyword webs, Route thinking paths, and Evolution over time. Use when Codex needs to prepare material for semantic search, turn temporary notes into permanent or project notes, build table-of-contents/index/search structures, create compact Chinese FIRE cards, or maintain this skill's original discussion thread provenance.

日本語の概要は準備中です。原文の説明を表示しています。