“bounded”的搜索结果

DDD v3 — bounded contexts, aggregates, value objects, domain events, Ubiquitous Language, strategic design

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Delegate reading large or multiple files to the `bulk-read` command, which sends the files to a cheaper reader model and returns only its answer. Use when a question needs the content of a file over about 350 lines or of several files at once, when a PreToolUse guard denied an unbounded read, or when the user says "bulk read", "一括読み込み", or "まとめて読んで". Do NOT use for files you are about to edit, for subtle correctness reasoning such as concurrency bugs, or for short files that fit a bounded read.

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Domain-Driven Design methodology using bounded contexts, ubiquitous language, and strategic/tactical patterns

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Analyzes bounded context boundaries in DDD projects. Detects cross-context coupling, shared kernel violations, context mapping issues, and ubiquitous language inconsistencies. Generates context map diagrams and boundary recommendations.

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Run a bounded, governed iteration — "loop", "iterate until", "keep going until", "sweep", "ratchet", "until it passes", "coverage to 100". Turns an open-ended autonomous run into a finite loop with checkpoints and explicit stopping conditions.

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Implements producer/consumer queues. Channel<T>, bounded/unbounded, backpressure, drain.

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Identifies domain modules, ownership boundaries, dependencies, and interfaces using Domain-Driven Design principles. Provides domain maps, bounded contexts, refactor recommendations. Use for "DDD", "domain modeling", "bounded contexts", or "service boundaries".

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在Parallels虚拟机中验证OpenClaw的安装、初始设置和更新，检查macOS、Windows及Linux的基本运行情况，并通过日志定位失败原因。

• 检查三个操作系统上的全新安装
• 验证OpenClaw更新流程
• 从现有快照恢复并重新验证

使用Python和Netmiko自动收集网络设备信息，协助编写或审查SSH脚本，加入连接数量限制、输出解析和错误处理，并为配置变更设置确认步骤。

• 收集多台设备的show命令输出
• 为审计记录接口和路由信息
• 调整SSH脚本的超时设置

检查Claude Code加载的智能体、技能、规则和MCP配置所占的信息量，估算词元数，找出过长或重复的定义，并按预计可削减的量为改进建议排序。

• 排查上下文迅速占满的原因
• 添加技能或MCP后检查配置
• 查找过长文件和重复指令

将性能优化拆解为现状测量、单个假设的方案比较和正确性验证，在时间与费用上限内选出测得最快且安全的方案，并保留可重复执行的命令、配置和记录。

• 通过测量优化缓慢操作
• 在相同输入条件下比较实现
• 评估响应时间、吞吐量和执行费用

将功能开发、重构和PR审查交给OpenCode CLI，跟踪长时间任务的进度、恢复会话，并汇报修改文件和测试结果，也支持在独立目录中并行执行。

• 委派功能开发和重构
• 审查PR中的缺陷与测试遗漏
• 监控并恢复长时间开发会话

在Paperclip中用文字指定要跟踪的工作，创建和更新状态卡片。通过限定条件搜索任务并生成摘要，集中呈现关注工作的进展。

• 了解发布准备的阻塞和待审核工作
• 汇总本周更新的任务
• 按项目或负责人查看进展

在启动前审查Homecore服务器的运行计划，检查身份验证、恢复顺序、功能测试、语音服务配置及配对机密信息的处理方式，不启动服务器。

• 审查Homecore启动计划
• 检查恢复顺序和限制值
• 启用Wasmtime或HAP前检查测试

帮助将claude-flow v3中职责过多的大型类按功能拆分，整理依赖关系、领域边界和事件协作，支持迁移到便于扩展功能与独立测试业务逻辑的结构。

• 按职责拆分大型类
• 设计任务、会话和监控边界
• 设计插件与事件协作

根据输出和运行环境排查终端命令失败或超时的原因。每次只调整一个相关条件后重试，并核实目标文件、进程或服务状态是否符合要求。

• 根据错误输出排查命令失败原因
• 检查依赖工具缺失或路径错误
• 检查超时的长时间运行任务

在现有TypeScript项目中，为集中维护业务规则的“聚合”创建代码骨架。配齐实体、持久化接口、领域事件和单元测试桩，为实现业务规则打下基础。

• 向现有业务领域添加聚合
• 为具有业务规则的概念建模
• 生成实体和测试代码骨架

检查采用领域驱动设计的 TypeScript 代码，查找跨业务领域的不当引用、数据一致性、事件及仓储位置问题，并汇总问题位置和改进建议。

• 审计业务领域间的依赖
• 合并前检查跨领域改动
• 在持续集成中检查设计边界

Plan an AI team around a goal, defining roles, deliverables, and a recorded unit budget. After approval, it creates team, run, and task records in RuFlo AI Team; it does not execute the work.

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• Plan roles for a new AI team
• Split a large goal into tasks with clear owners
• Organize a research, release, or security review team

帮助将claude-flow v3中职责过多的大型类按功能拆分，整理依赖关系、领域边界和事件协作，支持迁移到便于扩展功能与独立测试业务逻辑的结构。

• 按职责拆分大型类
• 设计任务、会话和监控边界
• 设计插件与事件协作

Review safety-sensitive Mole changes using documented bug patterns. Check how cleanup targets are selected, whether commands have time limits, whether cancellation stops later work, and whether dry runs match actual deletion plans.

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• Reviewing cleanup and uninstall safety
• Checking cancellation and command time limits
• Comparing dry-run plans with actual deletion

Build a catalog from multiple skill directories using an explicit priority order. Review duplicate names, selection decisions, and omitted entries before loading the instruction text of the chosen skill.

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• Cataloging project and user skill directories together
• Checking duplicate skill names before activation
• Reviewing catalog limits and omitted entries

Design and test rules for activating skills through human requests, AI selection, applications, or other skills. Check eligibility before matching descriptions, then return a JSON decision showing the selected channel, score, and policy reason.

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• Separate explicit requests from automatic skill selection
• Test allowed callers and skill composition limits
• Check cases where no skill should activate

Take implementation work through small, independently mergeable pull requests. Use a separate working directory for each PR, record manual QA evidence, write English review descriptions, resolve CI and review findings, then merge and clean up.

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• Deliver implementation work through pull requests
• Split a large task into small, independently mergeable PRs
• Build independent PRs concurrently