Results for “risk-acceptance”

Identify and prioritize risks by impact and controllability. Use for risk management, project planning, and strategic decision support.

Use when evaluating potential risks before making decisions, starting initiatives, or implementing changes. This skill provides a structured risk assessment framework for identifying, analyzing, and responding to risks across all domains.

Acceptance Eval

Map product assumptions by risk, confidence, evidence, and next validation step.

Generates structured Given/When/Then acceptance criteria for a user story or feature slice. Use when translating product requirements into testable scenarios that cover the happy path, edge cases, error states, and non-functional expectations for engineering handoff and QA.

UAT Sign-off

Use to monitor support conversations for conduct risk — pressure, mis-selling, unfair outcomes, obstruction and misleading statements — as distinct from whether the answer matched policy. Trigger for "monitor for mis-selling", "conduct risk in our support conversations", "are agents pressuring customers", "customers being obstructed from cancelling", conduct surveillance, or a conduct finding raised by second line.

Mental models and decision frameworks for building autonomous agents that continuously learn, explore, and accumulate skills in open-ended environments without human supervision

Broad risk assessment — key-person, technical, regulatory, competitive, financial, and execution risks beyond product/market

Use to build an account's cumulative support record ahead of a renewal or QBR, so the review reflects the whole relationship rather than the most recent ticket. Trigger for "prepare for this renewal", "what has this account's support experience been", "which accounts are at risk before renewal", QBR preparation, account health review, or an account that renewed badly with no warning.

在启动高风险项目或重要决策前，需要预先识别潜在失败点以增强心理韧性和方案鲁棒性时

在启动一个重要项目或关键行动之前，用于主动识别和防范风险

Create user acceptance test journeys from a target user's perspective, with role-based scenarios, acceptance criteria, and evidence capture

Strategic patterns for solving intractable problems through cascading approximation, self-improvement, and heterogeneous evaluation from DeepMind's AlphaGo system

Recommends a shared decision‑making process that provides patients with quantitative estimates of the expected weight effect of antidepressants to inform drug choice, also considering expected treatment length. Triggers include clinician questions such as ‘How should I discuss weight‑change risks with this patient starting an antidepressant?’ or ‘What tool can I use to show expected weight impact of sertraline vs bupropion?’.

Weekly churn risk detection across active client accounts. Scans for signals like decreased engagement, missed meetings, delayed payments, and competitor mentions. Scores risk 1-10 and outputs prioritized alert list.