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Two-layer memory architecture for board meeting decisions. Manages raw transcripts (Layer 1) and approved decisions (Layer 2). Use when logging decisions after a board meeting, reviewing past decisions with /cs:decisions, or checking overdue action items with /cs:review. Invoked automatically by the board-meeting skill after Phase 5 founder approval.
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Architecture Decision Records (ADR) — a lightweight method for capturing important architectural decisions with context, trade-offs, and rationale. Based on Michael Nygard's ADR pattern and Google/Meta/ByteDance's design documentation culture. USE WHEN: deciding between technology choices, designing new architecture, changing existing architecture, documenting why a decision was made, onboarding new team members, or preserving design context for future maintainers. Triggered by terms like "tech choice", "architecture decision", "why did we choose", "design rationale", "ADR", or "architectural decision record".
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为council整理的重要决策草案追加一次Codex外部批评，检查结论的薄弱之处、遗漏的失败情形，以及是否充分处理最有力的反对意见。
将无法独自判断的问题整理成供专家或相关人员填写的问卷。明确对方掌握的知识及所需答案，生成可在会议中共同填写或由对方自行回复的Markdown文档。
记录软件设计决策的理由及比较过的方案，整理README、API文档和变更日志，帮助后来加入的成员与AI智能体理解实现背景。
将城市绿地与树冠覆盖范围扩大的政策提案整理为HTML幻灯片，面向市议会和行政审查人员，清楚呈现公共需求、证据、政策选项及资金决策。
使用终端风格模板制作 HTML 幻灯片，说明 OpenDesign 中自带 API 密钥的模型选型，帮助技术团队判断成本、质量、连接方式及模型分工。
将访谈、客服工单、问卷和使用记录整理为用于产品或设计决策的HTML页面，集中展示证据、主题、可信程度、改进方案比较及下一步实验。
Create AgentDB learning plugins that use recorded experience to improve agent decisions. Choose a learning method, store states, actions, and rewards, train models, and evaluate suggested actions through CLI and API workflows.
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Create AgentDB learning plugins that use recorded experience to improve agent decisions. Choose a learning method, store states, actions, and rewards, train models, and evaluate suggested actions through CLI and API workflows.
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Work through project decisions one question at a time, with a recommendation and brief reasoning. Record each settled answer immediately in project documentation, keeping unresolved questions visible and documents marked as drafts until explicitly accepted.
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Work through project decisions one question at a time, with a recommended answer and a short explanation. Record settled choices in project documentation, including scope, completion criteria, constraints, risks, and unresolved questions.
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Make system architecture decisions by clarifying requirements and constraints, comparing benefits and drawbacks, and considering simpler alternatives. Record the reasoning in ADRs, architecture decision records, so significant choices and their rationale are documented.
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Make system design decisions by clarifying requirements, identifying constraints, and comparing the benefits and drawbacks of different approaches. Record the reasoning in architecture decision records, or ADRs, while considering simpler alternatives and the team's experience.
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Guide an agent through searching past decisions before work, saving new decisions with their reasons, and treating corrections as lessons. The workflow helps distinguish useful long-term knowledge from temporary details, code facts, and routine activity already captured by hooks.
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Examine strategic decisions through a structured meeting of AI agents representing executive roles. Gather independent recommendations, challenge assumptions, summarize disagreements, and record approved decisions with action owners and deadlines after the founder reviews the proposal.
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Store phase documents verbatim in MemPalace, organized as decisions, plans, or milestones. Avoid duplicate entries and mirror decision or delivery facts into a knowledge graph that records when those facts became valid.
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Design a GenLayer review workflow for agents acting on a blockchain. Define evaluation criteria, evidence formats, decision outputs, and the connection needed to turn review decisions into restrictions or revocation of delegated authority.
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Coordinate work across AI agents with shared rules for locating team files, recording decisions and their reasons, and requesting help. It also defines who owns revisions after a reviewer rejects an artifact.
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Turn existing research notes into an authoritative knowledge article after a team has made its decision. Records the outcome, rationale, trade-offs, and rejected alternatives while preserving source notes and links showing which documents the article replaces.
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Create AgentDB learning plugins that use recorded experience to improve agent decisions. Choose a learning method, store states, actions, and rewards, train models, and evaluate suggested actions through CLI and API workflows.
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Work through sixteen open questions in four rounds to clarify major product decisions, risky changes, or large refactors. The agent adapts later questions to earlier answers, then turns your decisions into a step-by-step implementation plan.
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Review important choices the agent made during the current work and identify those it remains unsure about. It considers overlooked alternatives and returns a concise list in plain English when explicitly requested by name.
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[omh] Previously rejected options to revisit: recall scoped reviewed rejected decisions without elevating them to approved memory. Use when the user says: decision-recall, rejected decision recall, rejected decisions, why was this rejected, previously rejected alternative, 거절된 결정, 기각된 대안.
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