「search skill」の検索結果

Search for vectors using semantic similarity. Requires authentication. Use for Agentuity cloud platform operations

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Detect AI/LLM-generated text patterns in research writing. Use when: (1) Reviewing manuscript drafts before submission, (2) Pre-commit validation of documentation, (3) Quality assurance checks on research artifacts, (4) Ensuring natural academic writing style, (5) Tracking writing authenticity over time. Analyzes grammar perfection, sentence uniformity, paragraph structure, word frequency (AI-typical words like 'delve', 'leverage', 'robust'), punctuation patterns, and transition word overuse.

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。

AgentDB Vector Search Optimization operates on 3 fundamental principles:

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。

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

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。

Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.

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。

Skill for discovering and researching autonomous AI agents, tools, and ecosystems using the AgentFolio directory.

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Advanced AgentDB Vector Search Implementation operates on 3 fundamental principles:

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。

Answer Engine Optimization (AEO) audit methodology for LLM visibility. Use when auditing brands for ChatGPT/Gemini mentions, checking LLM citations, analyzing AI search visibility, or when user mentions "AEO", "LLM visibility", "ChatGPT mentions", "Gemini citations", or "AI search optimization".

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Institution ratings, consensus price targets, EPS/revenue forecasts, finance calendar, shareholder data, fund holders, insider trades (SEC Form 4), short interest, industry rankings, peer group analysis via Longbridge. Frameworks: investment proposals, coverage initiation, stock research, competitive analysis, financial planning, and DeFi/on-chain analysis. Triggers: "机构评级", "目标价", "一致预期", "EPS预测", "内部人交易", "空头", "行业排名", "投资提案", "首次覆盖", "竞争格局", "财务规划", "DeFi收益", "链上数据", "機構評級", "目標價", "一致預期", "內部人交易", "空頭", "投資提案", "首次覆蓋", "競爭格局", "鏈上數據", "analyst rating", "price target", "consensus", "insider trades", "short interest", "coverage initiation", "DeFi yield", "on-chain", "earnings calendar", "finance calendar", "财报日历", "下周谁财报", "下周财报", "下周有哪些财报", "哪些财报", "谁财报", "FOMC", "非农", "股东", "谁持有", "股東", "基金持仓", "基金持倉", "機構評級", "目標價", "財務規劃"

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。

Read, search, and manage Confluence Cloud pages, spaces, blog posts, comments, attachments, and labels. Use this whenever the user wants to find a page, read a doc, search the wiki with CQL, create or update a page, add a comment, list pages in a space, pull an attachment, or ask "what does the wiki say about X" — even if they don't say "API". Also use it for any *.atlassian.net/wiki URL, or a CQL string when the context is wiki content rather than tickets. Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.

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。

Read, create, update, search, and associate HubSpot CRM records — contacts, companies, deals, tickets, and custom objects. Use this whenever the user wants to look up a contact, create a deal, update a company, search the CRM, link two records, or asks "what's in HubSpot" — even if they don't say "API". Also use it for any URL under app.hubspot.com or a mention of a HubSpot object/record ID. Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.

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。

Synthesize multiple per-competitor research files (produced by /competitor-research) into a single canonical threat matrix. Writes to marketing/competitors/aggregate.md as the locked canonical version every downstream skill reads. Triggers - "competitor aggregate", "synthesize competitors", "competitor matrix", "threat matrix", "lock competitor canonical"

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Build and query a local Markdown knowledge base ("vault"). TWO functions — (1) CONVERT raw files (PDF, Word/docx, PowerPoint/pptx, Excel/xlsx, csv/tsv, images, html, md/txt, json/yaml/code, audio/video) into clean Markdown with retrieval-friendly frontmatter; local-first (pandoc / python-pptx / openpyxl / pymupdf4llm / whisper), with cloud OCR (MinerU) only as a fallback. (2) ANSWER questions over the resulting vault with retrieval discipline — self-monitor coverage, flag missing/lossy content, and propose Maps-of-Content (MOCs). Triggers: "build/sync my local knowledge base", "convert these files to markdown for AI", "整理我的资料库", "把文件转成 md 给 AI 读", "本地知识库", "读我的本地 vault 回答", "这个主题我的资料里怎么说". Not for: one-off web research, or files that are already in a single doc you can read directly.

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。

Generate a topic-focused briefing in HTML from public news sources. Use when user asks for a briefing / observation / digest / 简报 / 观察 on any subject — region (Middle East, ASEAN, India), industry (semiconductors, EV supply chain, AI), policy issue (AI regulation, critical minerals, cross-border payments), institution (Fed, ECB, IMF), or theme. Output is a single self-contained HTML file with blue-color "TOPIC BRIEF" branding, optimized for both browser viewing and direct copy-paste into 微信公众号 / WeChat Official Account editor. Walks through 5 steps with one user confirmation midway. Do NOT use this skill for short summaries (<1000 字), single-piece news commentary, or already-defined report templates.

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。

Find unclaimed open source issues that match the user's skills and experience level. Searches for issues created by maintainers/org admins, checks contribution eligibility, and ranks by learning value. Use when looking for an issue to contribute to, starting OSS contributions, or finding GSoC-friendly issues. Not for finding problems that nobody has filed an issue for yet. Use oss-find-real-issues for that.

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。

Design system that makes HTML output look like a professional consulting deliverable instead of default AI styling. Use WHENEVER generating any HTML document — report, analysis memo, proposal, research summary, dashboard, artifact — and when the user says 「HTMLで資料」「HTMLでまとめて」「レポートにして」「コンサル風に」「資料っぽく」「デザインがダサい」 or asks to restyle existing AI-generated HTML. Replaces boxes, borders, gradients, emoji and rainbow colors with whitespace-driven, typography-first, print-ready (A4) design.

Odoo 17 development reference for Python models and ORM (search, domain, read_group, compute fields), XML/CSV data and views, OWL/JS client code, QWeb reports, security (ACL, record rules, groups), cron and server actions, migrations and module upgrades, tests, i18n, and performance. Use this skill whenever work involves Odoo 17 or custom addons, including traceback diagnosis, addons, manifests, XML errors, HTTP controllers, business rules, feature work, refactoring, or reviews.

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Odoo 18 development reference for Python models and ORM (search, domain, read_group, compute fields), XML/CSV data and views, OWL/JS client code, QWeb reports, security (ACL, record rules, groups), cron and server actions, migrations and module upgrades, tests, i18n, and performance. Use this skill whenever work involves Odoo 18 or custom addons, including traceback diagnosis, addons, manifests, XML errors, HTTP controllers, business rules, feature work, refactoring, or reviews.

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。

Retrieve Chinese AI news, recent topic search, event timelines and briefs from AIHOT's anonymous read-only Agent API. Use for current AI developments with original-source links.

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。

[Deprecated] discovery merged. Use `cm-skill-index` instead.

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Sync high-value dev knowledge (skills, decisions, lessons) into Google NotebookLM for cloud recall, podcasts, and flashcards. Pairs with Dockit/deep-search. Use for NotebookLM, nlm, knowledge base, skill sync, or cross-machine AI memory.

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Use GBrain to give OpenClaw or Hermes-style agents a local knowledge brain with markdown ingestion, entity links, hybrid search, scheduled consolidation, and MCP access.

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broot is a Rust-based terminal tool that provides a new way to see and navigate directory trees. It offers fuzzy search, file preview, git status integration, and an interactive tree view that adapts to your terminal size.

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Bright Data Web MCP gives MCP-compatible agents live web search, scraping, and optional browser-automation access through Bright Data’s web-access platform. It is built for agents that need current information, anti-bot resilience, and structured extraction without maintaining their own scraping stack.

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。