「iso」の検索結果

競合との違いが伝わらない製品の訴求を見直し、顧客に響く市場での立ち位置を整理するスキル。競合比較や強みの評価から、表現の比較テスト、段階的な展開までを支援します。

• 競合との違いを明確にしたいとき
• 見出しや営業表現を検証したいとき
• 訴求変更を段階的に進めたいとき

Collaboration profile for Quinn: curious, energetic, and implementation-focused partnership patterns for Ember sessions with Alison.

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。

C#の単体テストをXUnitで書く際に、基本構成から複数データでの検証、例外の確認、依存先の切り離しまで、読みやすく独立したテスト作りを支援するスキル。

• C#のXUnitテスト環境の整備
• Theoryとデータ属性による複数入力の検証
• 例外の確認とモックによる依存先の分離

Prepare for due diligence meetings — management presentations, expert network calls, customer references, and advisor sessions. Generates targeted question lists, benchmarks to reference, and red flags to probe. Use before any diligence meeting or call. Triggers on "prep for management meeting", "diligence call prep", "expert call questions", "customer reference questions", or "meeting prep for [company]".

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。

Verify changes to the claude-for-msft-365-install admin scripts and commands by driving them against an isolated fake $HOME.

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。

Framework for building competitive landscape decks — market positioning, competitor deep-dives, comparative analysis, strategic synthesis. Use when the user asks for a competitive landscape, competitor analysis, peer comparison, market positioning assessment, strategic review, or investment memo deck. Also triggers on "who are the competitors to X", "benchmark X against peers", "build a market map", or any request to systematically evaluate competitive dynamics across an industry.

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。

Structured visual QA verdict for screenshot-to-reference comparisons

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。

Process-first advisor routing for Claude, Codex, Gemini, Antigravity, Grok, Cursor, or Muse via `omc ask`, with artifact capture and no raw CLI assembly

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。

Performance attribution analysis — Brinson sector/stock-selection attribution, factor alpha/beta decomposition, market-timing evaluation, and benchmark comparison framework.

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。

DeFi yield analysis and optimization — lending rates, LP yields, staking returns, yield farming strategies, risk-adjusted yield comparison, and protocol-level sustainability assessment.

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。

Professional finance research toolkit — backtesting (11 engines + benchmark comparison panel), factor analysis, Alpha Zoo (478 pre-built alphas across qlib158/alpha101/gtja191/academic/fundamental), options pricing, 90 finance skills, 30 multi-agent swarm teams, Trade Journal analyzer, and Shadow Account (extract → backtest → render) across 29 market-data sources (tushare, yfinance, okx, binance, akshare, baostock, tencent, mootdx, ccxt, futu, mt5, tickerall, local, eastmoney, sina, stooq, yahoo, pykrx, india_broker, qveris, longbridge, nobitex, wallex, plus optional-key finnhub/alphavantage/tiingo/fmp/gildata).

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。

女娲造人：输入人名/主题/甚至只是模糊需求，自动深度调研→思维框架提炼→生成可运行的人物Skill。 两种入口：(1)明确人名→直接蒸馏 (2)模糊需求→诊断推荐→再蒸馏。 触发词：「造skill」「蒸馏XX」「女娲」「造人」「XX的思维方式」「做个XX视角」「更新XX的skill」。 模糊需求也触发：「我想提升决策质量」「有没有一种思维方式能帮我...」「我需要一个思维顾问」。 English triggers: "distill [person]", "nuwa", "create a [person] perspective skill", "how does [person] think", "I need a thinking advisor".

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。

Triage npm packages and lockfiles for install-script malware, credential exfiltration, and worming behavior using GuardDog, manual tarball inspection, and dynamic detonation with network/filesystem monitoring. Use when vetting a new dependency, reviewing a package.json/package-lock.json during code review, checking lockfiles against a supply-chain advisory's known-bad versions, or investigating a host suspected of installing a trojanized package.

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。

Detect NTLM relay attacks (T1557.001) by correlating Windows Event 4624 LogonType 3 for IP-to-hostname mismatches, identifying Responder/LLMNR poisoning artifacts, auditing SMB/LDAP signing, and flagging NTLMv2-to-NTLMv1 downgrades. Use for hunting credential relay in NTLM-enabled AD, investigating auth-source anomalies, building SIEM correlation rules, or responding to PetitPotam/DFSCoerce/PrinterBug alerts.

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。

Detects typosquatting attacks in npm and PyPI package registries by analyzing package name similarity using Levenshtein distance and other string metrics, examining publish date heuristics to identify recently created packages mimicking established ones, and flagging download count anomalies where suspicious packages have disproportionately low usage compared to their legitimate targets. The analyst queries the PyPI JSON API and npm registry API to gather package metadata for automated comparison. Activates for requests involving package typosquatting detection, dependency confusion analysis, malicious package identification, or software supply chain threat hunting in package registries.

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。

Detect UEFI Secure Boot bypasses and bootkits such as BlackLotus and Bootkitty by verifying Secure Boot state, checking dbx revocation currency, and hashing EFI boot binaries against known-bad sets using mokutil, efi-readvar/dbxtool, CHIPSEC, sbverify/pesign, and Windows Confirm-SecureBootUEFI. Use when auditing fleet dbx rollout after a bootkit advisory or hunting for pre-OS persistence on a suspected-compromised endpoint.

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 covers detecting cyber attacks targeting Supervisory Control and Data Acquisition (SCADA) systems including man-in-the-middle attacks on industrial protocols, unauthorized command injection into PLCs, HMI compromise, historian data manipulation, and denial-of-service against control system communications. It leverages OT-specific intrusion detection systems, industrial protocol anomaly detection, and process data analytics to identify attacks that traditional IT security tools miss.

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。

Run a targeted spearphishing simulation for initial access by developing OSINT-derived pretexts, building payloads (HTML smuggling, macro docs, ISO/LNK, OneNote, QR codes), standing up look-alike-domain email infrastructure with SPF/DKIM/DMARC via GoPhish, and tracking results. Use in authorized engagements to gain initial access via personalized phishing against specific individuals, distinct from broad campaigns.

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。

Conduct a defensible cybersecurity risk assessment using the NIST SP 800-30 Rev 1 methodology: prepare scope and a risk model, identify threat sources and threat events, identify vulnerabilities and predisposing conditions, determine likelihood and impact, compute risk, and communicate results as a prioritized risk register. Use when an organization needs an actual risk *assessment* (not a maturity score), when a control framework (CSF, ISO 27001, RMF, SOC 2, PCI) requires a documented risk analysis as input, when leadership asks "what are our top risks and how bad are they", when assessing risk for a new system or major change, or when building a risk register from scratch. This is the methodology that feeds framework selection, ATO packages, and treatment decisions. Keywords: risk assessment, NIST 800-30, threat modeling, likelihood and impact, risk register, risk analysis, threat sources, vulnerabilities, risk determination, qualitative risk, risk matrix, residual risk, risk treatment.

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。

Build structured communication templates for malware incidents (ransomware, wiper, trojan, worm), covering internal stakeholder notifications, executive briefings, technical advisories for IT teams, customer notifications, and regulatory disclosures, with severity-based escalation procedures. Use when drafting or standardizing incident communications and notification workflows for a malware outbreak.

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。

Builds a structured SOC incident response playbook for ransomware attacks covering detection, containment, eradication, and recovery phases with specific SIEM queries, isolation procedures, and decision trees. Use when SOC teams need formalized response procedures for ransomware incidents aligned to NIST SP 800-61 and MITRE ATT&CK ransomware techniques.

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。

Establish a repeatable operational process for triaging, testing, and deploying Microsoft Patch Tuesday security updates (Windows, Office, Exchange, SQL Server, Azure) via WSUS/SCCM within risk-based remediation SLAs, from advisory review through validation. Use when building or improving a monthly patch management workflow or prioritizing which CVEs to remediate first.

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。

Respond to security incidents in AWS, Azure, and GCP via identity-based containment, cloud-native log analysis (CloudTrail, Azure Activity Logs, GCP Audit Logs), resource isolation, and forensic evidence acquisition adapted for ephemeral cloud infrastructure. Use when CSPM alerts or audit logs show compromised cloud credentials, unauthorized IAM changes, or a breach spanning cloud services.

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。

Collect volatile forensic evidence from a compromised host by following the order of volatility, preserving memory, network connections, running processes, and system state with documented chain of custody before they are lost. Use before isolating, shutting down, or remediating a compromised host, especially when fileless or memory-resident malware is suspected, root cause analysis is needed, or the evidence must hold up in legal proceedings.

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。