2.7천건 · 관련도순
"Calculate Value at Risk to estimate maximum portfolio loss at a given confidence level. Use this skill when the user needs to quantify downside risk, set risk limits, or report regulatory risk measures — even if they say 'worst case loss', 'portfolio risk', or 'how much could we lose'.".
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Maintain a centralized living risk register across projects. Use this skill when: - You need to create or update a risk register for a project or feature - You want to consolidate risks from individual specs into one register - You need to review and update risk status, mitigations, and owners - You want a cross-project risk view
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Reads a risk register together with meeting notes and incident reports and returns a draft update pack: existing risks whose exposure, controls, ownership or status the sources say have changed, new risk candidates, closure candidates, and the one owner decision each item needs. Never assigns or changes a likelihood, impact, score or colour and never edits the register; owners decide. Use when the user asks to "update the risk register from these minutes", "refresh the register with the incidents since the last review", "reconcile the register against the notes" or "what changed on our risks". Do not use for writing up an incident itself, use incident-postmortem-drafter or data-incident-impact-brief instead; to track actions from minutes, use corrective-action-tracker. Drafts for human review; never approves, authorises or signs off.
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Knowledge base from NIST SP 800-37 Revision 2, the Risk Management Framework (RMF) for information systems and organizations. Use for the seven RMF steps (Prepare, Categorize, Select, Implement, Assess, Authorize, Monitor) and their tasks; the three-tier organization-wide risk model; authorization boundaries; the requirements-to-controls relationship; security categorization (FIPS 199/200 high-water mark) and control selection/tailoring (SP 800-53/53B baselines); assessment, the authorization decision and risk acceptance, continuous monitoring and ongoing authorization; the security/privacy distinction; and supply chain risk management. This is the security-and-privacy-risk-governance edge of systems engineering — it governs how much protection and whether to accept residual risk, complementing the disciplines that decide how protection is built. Does NOT reproduce the SP 800-53 control catalog or its baselines, the FIPS impact tables, or the ISO/IEC/IEEE 15288 process text; it names and routes to them rather than restating them.
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Knowledge base from the NASA Probabilistic Risk Assessment Procedures Guide (NASA/SP-2011-3421, 2nd ed.). Use for quantitative PRA of aerospace and safety-critical systems: the risk triplet and scenario logic stack (MLD, ESD, event trees, fault trees, minimal cut sets), Bayesian data collection and parameter estimation, aleatory/epistemic uncertainty modeling and common-cause failure (Alpha Factor, beta-factor, CCBE), human reliability analysis (THERP, CREAM, NARA, SPAR-H), context-based software risk (CSRM), physics-based and structural/phenomenological models (stress-strength, limit states, FORM/SORM, NASGRO, range safety), uncertainty propagation and importance measures (F-V, RAW, Birnbaum, DIM), and launch-abort modeling with worked PRA examples. This is the QUANTITATIVE engine beneath NASA's risk doctrine — for the qualitative RIDM/CRM decision framework use the nasa-risk pack. Thin on programme management, organisational risk governance, and non-aerospace regulatory contexts; aerospace-focused and anchored to the 2011 second edition.
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Assess investment risk from supplied daily returns, summarize potential losses and drawdowns, estimate position sizes from backtest results, and review trading halt conditions. Save the assessment for later reference, with assumptions clearly stated.
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Assess a repository without changing it and report its type, suggested agent roles, risk, MCP connections, test confidence, and publication readiness. Use the results for setup decisions, comparisons over time, or automated risk checks in CI.
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Rank problems and proposed fixes using four scored criteria: expected benefit, implementation cost, deployment ease, and risk. The skill produces a sorted priority table with scoring rationales and explains why the top three items should come first.
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Build a tracking system for vulnerabilities that cannot be fixed on time. Define exception requests, approval workflows, alternative protective measures, expiration checks, and audit records so teams can track accepted risks and support compliance reviews.
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Plan security programs for growing companies by estimating financial risk and prioritizing controls. Produce compliance roadmaps, budget justifications, incident response plans, vendor assessments, and board reports that connect security decisions to business impact.
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Analyze SaaS customer data with three Python tools that calculate account health, rank churn risk, and prioritize expansion opportunities. Use repeatable weighted scores to plan customer outreach and prepare quarterly business reviews.
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Support startup AI strategy by comparing API use, fine-tuning—additional training of an existing model—and in-house development. Assess three-year costs, regulatory risk, self-hosting breakeven points, and hiring priorities to inform leadership decisions.
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Calculate portfolio risk metrics including VaR, CVaR, Sharpe, Sortino, and drawdown analysis. Use when measuring portfolio risk, implementing risk limits, or building risk monitoring systems.
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Assess physical and transition climate risk for a site, product, or portfolio with scenario-based structure. Use when asked to run a climate risk assessment, evaluate physical or transition risk, prepare TCFD/ESRS-style climate risk analysis, or assess how climate scenarios affect an asset or business. Produces a hazard-exposure-vulnerability matrix across 2030/2040/2050 horizons and labelled scenarios, with financial-impact ranges, confidence levels, and adaptation options.
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Expert DORA (Regulation (EU) 2022/2554 — Digital Operational Resilience Act) compliance advisor for EU financial entities. Use this skill whenever a user asks about DORA compliance, ICT risk management frameworks, ICT incident classification or reporting, threat-led penetration testing (TLPT), ICT third-party risk management, Register of Information, contractual provisions with ICT providers, ICT concentration risk, oversight of critical ICT third-party service providers (CTPPs), or any DORA RTS/ITS obligation. Also trigger for: "DORA gap analysis", "DORA readiness", "Art. 6 ICT risk framework", "Art. 17 incident reporting", "Art. 26 TLPT", "Art. 28 third-party policy", "Art. 30 contractual provisions", "Register of Information CIR 2024/2956", "critical TPSP designation", "DORA vs NIS2", "DORA simplified framework", or EBA/ESMA/EIOPA digital resilience guidance.
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Expert third-party risk management (TPRM) advisor — a vendor risk analyst for the full lifecycle: risk-based vendor tiering, tailored due-diligence questionnaires (SIG-style or mapped to ISO 27001, SOC 2, DORA, NIS2, HIPAA), SOC 2 Type II report review (exceptions, carve-outs, CUECs, bridge letters), DPA and sub-processor review under GDPR Art. 28, contract security addenda (DORA Art. 30 provisions), ongoing monitoring programmes, and vendor offboarding. Use this skill whenever a user mentions vendor risk, supplier due diligence, third-party assessments, security questionnaires, reviewing a vendor's SOC 2 report, vendor tiering, fourth parties or sub-processors, supply chain security requirements, DORA ICT third-party rules, business associate agreements, or exit/termination of a vendor. Also trigger for 'a customer sent us a questionnaire' and 'how do I assess this vendor' style requests.
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Expert NIST AI Risk Management Framework (AI RMF 1.0) advisor covering all four functions: GOVERN, MAP, MEASURE, MANAGE. Use this skill whenever a user asks about NIST AI RMF, AI risk management, AI trustworthiness, GOVERN function, MAP function, MEASURE function, MANAGE function, AI RMF Playbook, AI risk profiles, responsible AI, AI bias management, AI transparency, AI explainability, AI reliability, AI safety, NIST AI 100-1, AI risk assessment, AI incident response, or alignment to EU AI Act, ISO 42001, or NIST CSF via AI RMF. Trigger even if the user doesn't say "skill" — any NIST AI RMF or AI governance risk question should use this skill.
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Classify AI systems under the EU AI Act (Regulation (EU) 2024/1689) and determine compliance obligations. Use when asked to assess AI risk level, check if an AI system is prohibited, determine high-risk status, identify GPAI model obligations, map provider/deployer responsibilities, or build an AI Act compliance roadmap. Covers the full classification decision tree (Prohibited → High-Risk → Limited → Minimal → GPAI), obligations by role (provider, deployer, importer, distributor), compliance timelines, and DACH-specific considerations (German works council, BaFin, BSI, BNetzA). Triggers on phrases like "classify this AI system", "is this high-risk under the AI Act", "AI Act risk assessment", "EU AI Act compliance", "prohibited AI practice", "GPAI obligations", "AI Act timeline".
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Assess and operationalize implementation readiness for high-risk AI systems under the EU AI Act Annex III, including provider and deployer obligations, conformity assessment, post-market monitoring, and EU database registration. Use when users say things like “we classified this as high-risk, what now?”, “build an EU AI Act readiness plan”, “assess our Annex III compliance gaps”, “what do providers/deployers of high-risk AI need to implement?”, “prepare for conformity assessment”, or “create a high-risk AI implementation roadmap.”
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Create YOUR personal guarantee on top of the product's guarantee for risk reversal. Triggers on: "create a guarantee", "guarantee for my affiliate", "risk reversal", "money back guarantee", "what guarantee can I offer", "reduce buyer risk", "guarantee copy", "how to guarantee", "affiliate guarantee", "personal guarantee", "risk-free offer", "satisfaction guarantee", "results guarantee".
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Apply the NIST AI Risk Management Framework (AI RMF 1.0) and adjacent guidance to AI / ML systems — model lifecycle governance, fairness and bias evaluation, robustness, transparency, accountability, third-party model risk, monitoring for drift, and AI incident response. Broader than prompt-injection (which is the security slice). Use when the user mentions 'AI risk,' 'AI governance,' 'NIST AI RMF,' 'AI compliance,' 'ML governance,' 'model risk management,' 'AI fairness,' 'AI bias,' 'algorithmic accountability,' 'AI Bill of Rights,' 'EU AI Act,' 'AI transparency,' 'model card,' 'AI red team,' 'AI safety,' 'responsible AI,' 'model drift,' 'concept drift,' 'AI monitoring,' 'AI incident,' or needs to assess or govern an AI / ML system.
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Preparing EU AI Act compliance documentation for high-risk AI systems. Covers Annex III classification, technical documentation under Art. 11, conformity assessment, risk management systems, and CE marking requirements. Keywords: EU AI Act, high-risk AI, Annex III, conformity assessment, CE marking.
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Detect and search for similar utility/invention patents based on product information. Trigger when users mention utility patent detection, patent infringement risk, patent similarity search, patent screening, invention patent search, patent risk assessment, TRO (Temporary Restraining Order) risk analysis, utility patent, invention patent detection, patent infringement risk, patent search, TRO risk, Ruiguan. Even if the user does not explicitly say "utility patent", trigger this skill whenever their need involves checking whether a product may infringe existing utility/invention patents before selling in a target market.
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Churn risk identification and intervention — scans health signals for at-risk accounts, classifies risk level (CRITICAL/HIGH/MEDIUM), and produces an intervention sequence per risk type. Use when asked to "find at-risk accounts", "who might churn", "build a churn prevention plan", "identify churn signals", or "rescue this account".
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