「ngs」の検索結果

Djangoアプリのログイン、権限、入力処理、本番設定を点検します。不正な操作やスクリプト実行への対策から、ファイル投稿とAPIの保護まで見直すスキル。

• ログインと利用者権限のレビュー
• 公開前に本番設定を点検したいとき
• 入力処理やリクエスト保護の見直し

Use when the user wants to customize keyboard shortcuts, rebind keys, add chord bindings, or modify ~/.claude/keybindings.json. Examples: "rebind ctrl+s", "add a chord shortcut", "change the submit key", "customize keybindings".

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。

Make sure to use this skill whenever the user mentions anything related to Danish job listings, job search in Denmark, finding work in Denmark, or job vacancies on Jobdanmark — even if they don't explicitly mention jobdanmark.dk. Also invoke this skill for questions about specific Danish job categories, municipalities, job types, or salaries in a job-search context. Trigger phrases include: danish jobs, jobs in denmark, find job denmark, job search denmark, danish job listings, jobdanmark, job opslag, find job, jobsøgning, ledige stillinger, stillingsopslag, job i Danmark, fuldtidsjob, deltidsjob, studiejob, praktikplads, elev, fleksjob, IT job denmark, sygeplejersker job, håndværker job, ingeniør job, pædagog job, kontor job, leder job, salg job, hotel job, kirke job, job aarhus, job københavn, job odense, job aalborg, job sjælland, job jylland, job fyn, jobkategorier denmark, ledige job, ansøgningsfrist, søg job, job opslaget, jobopslag, danish vacancies, work in denmark, employment denmark, job denmark, jobs near me denmark, apprentice denmark, internship denmark, part-time denmark, full-time denmark.

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。

Earnings estimate revisions, guidance analysis, and post-earnings drift (PEAD) — track analyst consensus changes, earnings surprise patterns, and management guidance shifts for US/HK equities.

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 vector embeddings via 9Router /v1/embeddings using OpenAI / Gemini / Mistral / Voyage / Nvidia / GitHub embedding models for RAG, semantic search, similarity. Use when the user wants embeddings, vectors, RAG, semantic search, or to embed text.

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。

Analyzes meeting transcripts and recordings to surface behavioral patterns, communication anti-patterns, and actionable coaching feedback. Use this skill whenever the user uploads or points to meeting transcripts (.txt, .md, .vtt, .srt, .docx), asks about their communication habits, wants feedback on how they run meetings, requests speaking ratio analysis, mentions filler words or conflict avoidance, or wants to compare their communication across time periods. Also trigger when users mention tools like Granola, Otter, Fireflies, or Zoom transcripts. Even if the user just says "look at my meetings" or "how do I come across in meetings" — 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。

Persistente dateibasierte Planung für mehrstufige Arbeit mit KI-Agenten. Hält task_plan.md, findings.md und progress.md auf dem Datenträger; Lebenszyklus-Hooks speisen ausgewählten Planungskontext des Projekts ein. Die automatische Wiederherstellung liest nur die Planungsdateien des Projekts. Nur ein ausdrücklicher Aufruf von session-catchup.py --metadata darf lokale Sitzungsmetadaten desselben Projekts prüfen; --replay darf begrenzte, nonce-gerahmte Auszüge ausgeben. Der optionale Gate-Modus kann nur bei Unterstützung durch den Host eine Fortsetzung anfordern und führt niemals in Markdown angegebene Befehle aus. Der Skill hat keinen Netzwerk-Uploadpfad. Verwenden für Forschung oder Arbeit mit mehr als 5 Tool-Aufrufen.

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。

Review Apache ShardingSphere or user-authorized downstream pull requests and PR discussions from public or authorized repository evidence. Use for code-correctness or mergeability decisions, CI-focused review, root-cause and regression analysis, complete consolidated findings, copy-ready committer feedback, challenged findings, multi-round review, and formal review of local implementation candidates in the repository completion loop.

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 and update the Superset desktop app's user settings (theme, fonts, terminal, git, notifications, behavior) via the superset CLI, including creating and installing custom themes from JSON. Use when asked to change app settings, switch or create a theme, adjust fonts, or configure desktop preferences without opening the settings UI.

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。

Reads and changes a running CARLA server's WorldSettings via apply_settings — synchronous vs asynchronous mode, fixed_delta_seconds (fps), physics substepping, and no_rendering_mode — and keeps the Traffic Manager's sync state matched automatically. Use when the user asks to "enable/disable sync mode", "set synchronous mode", "run at a fixed fps/step", "turn off rendering", "make the sim deterministic", or "restore async mode", and as the prerequisite for keeping settings across a map load.

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。

Search LinkedIn job listings and extract full job details. Supports filtering by work type (remote/on-site/hybrid), contract type (full-time/part-time/contract/internship), experience level, date posted, and company. Returns job title, company, location, work type, contract type, experience level, posted date, applicant count, job description, salary, and direct job URLs. Use when user mentions linkedin jobs, linkedin job search, scrape linkedin jobs, extract linkedin job listings, find jobs on linkedin, job openings, job postings linkedin, linkedin career search, job hunting linkedin, linkedin vacancy, jobs remote linkedin, work from home jobs linkedin, linkedin scraper jobs, linkedin job data, linkedin hiring, collect job leads linkedin.

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。

Scrape job listings from Indeed.com by keyword, location, and country. Returns job title, company, salary, rating, description, benefits, and apply links. Use when user mentions Indeed, Indeed scraper, Indeed jobs, scrape Indeed, job search Indeed, Indeed job listings, extract Indeed data, Indeed job data, get jobs from Indeed, Indeed employment data, job market research Indeed, Indeed salary data, bulk job extraction Indeed, Indeed job scraper, monitor Indeed listings, Indeed hiring data, job postings Indeed, Indeed career search. Also applies to: job market analysis, salary benchmarking from Indeed, competitor hiring monitoring, recruitment data collection, building job databases from Indeed search results.

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。

eBay sold-listings scraper across 8 marketplaces (ebay.com/.co.uk/.de/.fr/.it/.es/.ca/.com.au). Takes keyword plus filters (category, price range, item condition, item location, sort order, completed toggle) and returns paginated real-sale records with itemId, url, title, condition, conditionId, endedAt, soldPrice, soldCurrency, listingType (best_offer_accepted / buy_it_now / auction), isBestOfferAccepted, buyingFormat, bidCount, shipping, totalPrice, thumbnails, seller info, sellerType. Use when user mentions ebay sold, ebay sold listings, ebay sold prices, ebay completed listings, ebay comps, ebay resale prices, ebay auction sold results, ebay best offer accepted, scrape ebay sold, ebay market research, ebay pricing intelligence, ebay flipping research, real sold prices ebay, get sold prices from ebay. Also applies to price benchmarking, sold-price analytics, resale valuation, cross-marketplace price arbitrage, appraisal for collectibles, brand demand tracking on ebay.

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 before answering or editing whenever an MSTest v1/v2 project is being upgraded or repaired for v3. Triggers include QualityTools assembly references; MSTest.TestFramework/TestAdapter 1.x-2.x; "upgrade to MSTest v3"; comparing v1 and v2 migration paths; choosing MSTest or MSTest.Sdk; CS0411/CS1503 after a v3 package bump; DataRow type mismatch, MSTEST0014, or "Test data doesn't match method parameters"; .testsettings/LegacySettings to .runsettings; timeout changes; and net5.0 or other dropped v3 TFMs. Still use it when packages say 3.x but migration source errors or legacy settings remain. Preserve VSTest/MTP. Do not use for a clean v3 project, v3-to-v4, framework conversion, or runner-only migration.

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。

Python library for accessing, analyzing, and extracting data from SEC EDGAR filings. Use when working with SEC filings, financial statements (income statement, balance sheet, cash flow), XBRL financial data, insider trading (Form 4), institutional holdings (13F), company financials, annual/quarterly reports (10-K, 10-Q), proxy statements (DEF 14A), 8-K current events, company screening by ticker/CIK/industry, multi-period financial analysis, or any SEC regulatory filings.

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。

Fetch financial and market data with the yfinance Python library (Yahoo Finance). Use this skill whenever the user wants stock data: current quotes and price history, financial statements (income statement, balance sheet, cash flow), options chains, dividends and splits, earnings and analyst estimates, price targets and ratings, institutional and insider holdings, news, multi-ticker comparisons, stock screens, or sector and industry data. Use it even when the user gives only a ticker symbol (AAPL, MSFT, TSLA) and the intent has to be inferred. For earnings previews or recaps, estimate revisions, valuation, correlation, liquidity, or ETF premium analysis, prefer the dedicated 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。

Guides the end-to-end AWS resilience lifecycle integrating Resilience Hub v2, Fault Injection Service, and Application Recovery Controller. Covers the Define → Test → Operate workflow: from policy creation through failure mode assessment, to FIS experiment validation, to ARC operational controls. Applicable when the user wants a complete resilience strategy, needs to connect findings to experiments to controls, or is planning a resilience program. Also applicable for the meta question of whether marking NGRH findings as resolved is enough, whether they are "done" after resolving findings, or how to validate findings before resolving them. Not applicable for resolving or remediating a specific individual finding (see resilience-hub-failure-mode-assessment), or when a single service is explicitly named (e.g. "what FIS experiment should I run").

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。

List recent meetings and voice memos. Use when the user asks "what meetings did I have", "show my recent recordings", "any meetings today", "list my voice memos", or wants an overview of their meeting history. Also use when they need to find a specific meeting by browsing rather than searching.

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。

Self-coaching analysis of your own behavior across meetings — talk-time ratio, filler words, hedging language, monologue length, energy patterns, and (when meetings are tagged via /minutes-tag) what your behavior in winning meetings looks like vs losing ones. Use this whenever the user says "how did I do", "review my last meeting", "mirror", "self-review", "show my patterns", "coach me", "where am I weak", "talk time", "am I improving", "what do I do in meetings I win", "feedback on me", or asks for any kind of personal feedback on their own meeting behavior. This is the rare skill that gives the user a mirror to their own habits — surface it whenever they show curiosity about their own performance, even if they don't use the word "mirror".

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。

Extract facts from meetings and update your knowledge base — person profiles, chronological log, and index. Use when the user asks "ingest my meetings", "update my knowledge base", "extract facts from meetings", "sync meetings to wiki", "backfill knowledge", or wants their PARA/Obsidian/wiki profiles updated from conversation 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。

Read status and send commands to Samsung SmartThings devices: lights, locks, thermostats, sirens, garage doors. Trigger phrases: smartthings, samsung smart home, unlock the door, smartthings thermostat.

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。

All-in-one project configuration and health management. Sets up new projects (settings.local.json, CLAUDE.md, .gitignore), audits existing projects (permissions, context quality, MCP coverage, leaked secrets, stale docs), tidies accumulated cruft, captures session learnings, and adds permission presets. Uses sub-agents for heavy analysis to keep main context clean. Trigger with 'project health', 'check project', 'setup project', 'kickoff', 'bootstrap', 'tidy permissions', 'clean settings', 'capture learnings', 'audit context', 'add python permissions', or 'init project'.

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。

Automatically invoke this skill whenever the user asks about Fabric tenant settings or Power BI tenant settings or auditing tenant settings. You can use this skill if the user mentions "Fabric administration".

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 current trends and challenges in Japanese NLP for a topic. Surveys the existing awesome-japanese-nlp-resources dataset and augments it with up-to-the-minute web research to produce a combined trend + issue report. Use only when the user explicitly wants a trend/landscape report, a challenges/limitations report, or a general research overview of a Japanese NLP topic (this combines the bundled dataset with live web research). Trigger phrases include '日本語LLMの最新トレンド', '〜の動向をまとめて', '最近の日本語NLPの流れ', '日本語LLMの課題', '〜の問題点・限界', '未解決の論点', 'trend report on Japanese embeddings', 'latest Japanese speech models', 'challenges in Japanese NER', 'limitations of Japanese embeddings'. For a simple lookup use the search skill; this one runs web research.