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Expert product specification and documentation writer. Use when creating PRDs, user stories, acceptance criteria, technical specifications, API documentation, edge case analysis, design handoff docs, feature flag plans, or success metrics. Covers the full spectrum from high-level requirements to implementation-ready specifications.
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Transforms vague UI/feature requests into structured, optimized prompts with design system awareness. Use when generating prompts for UI implementation, feature specification, or design-to-code translation. Triggers on tasks requiring prompt refinement, UI specification, or design system integration.
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Extract an Allium specification from an existing codebase. Use when the user has existing code and wants to distil behaviour into a spec, reverse engineer a specification from implementation, generate a spec from code, turn implementation into a behavioural specification, or document what a codebase does in Allium terms.
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Generate tests from Allium specifications. Use when the user wants to propagate tests, generate test files from a spec, write tests for a specification, create property-based tests, produce state machine tests, check test coverage against spec obligations, or understand what tests a specification requires.
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Write the executable feature specification — the WHAT and WHY artifact that agents and reviewers treat as source of truth. Owns both /specify and /clarify modes. Load when the user asks to write a feature spec, write a specification, write an executable spec, define functional requirements, capture acceptance criteria as Given/When/Then, or when the spec-driven-development orchestrator routes here. Also triggers on "feature spec", "executable spec", "/specify", "/clarify", "write the spec for this feature", "specification for", "spec-driven", "machine-readable spec". Output: docs/specs/YYYY-MM-DD-<slug>-feature-spec.md. Hard gate: cannot Approve while [NEEDS CLARIFICATION] markers remain.
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将规格或需求整理成实施计划，明确要修改的文件、函数定义、测试和验证步骤。在编写代码前拆分工作，形成可交给其他人员或代理执行的任务。
将实施计划中的任务逐一交给不同的代理，检查是否符合规格要求以及代码质量，并将进度记录到文件中，最后审查整个分支的全部变更。
通过附有建议答案的问题，梳理工作和生活中的重复任务，明确启动条件、人工确认环节及决策摘要，形成实施人员无需追加提问即可据此构建的工作流规格。
将计划、规格或对话拆分为可独立验证行为的小型开发任务，明确依赖关系、实施顺序和验收条件，经用户确认后保存为本地文件或登记到任务管理工具。
根据现有对话和对代码库的理解编写规格文档，并发布到项目的问题跟踪系统，整理用户问题、需求、实现决策、测试方针及本次不涵盖的范围。
读取规格说明和相关工单的依赖关系，安排多个代理推进实现。经过测试、代码审查和问题修正后，将成果汇总到一个集成分支，并完成工单处理。
将规格文档或工单中的任务落实为代码，定期进行类型检查和测试，完成后使用code-review技能审查变更，并提交到当前分支。
将模糊的功能需求或影响较大的变更整理为验收标准或交接资料，明确范围、前提、风险、预期行为与验证方法，并检查现有规格中的遗漏和矛盾。
先确定前后端或服务间共享的API与事件数据规范，再生成类型，并按同一规范验证测试数据和实际响应，通过共同审查变更，减少并行开发中的字段偏差与兼容性问题。
将实施计划中的任务分别交给上下文独立的子智能体，先检查是否符合规格，再审查代码质量。发现问题后反复修正和复查，最后检查各部分的集成情况。
通过对话完成提案、规格文档和决策记录，从梳理背景、逐节起草到读者验证。让不了解写作过程的Claude阅读，找出解释不足和含糊之处。
通过五个阶段，将模糊需求整理成可用于实现的具体规格，并创建GitHub议题；还可按需建立独立工作目录，启动Claude Code进行实现。
Turn specifications into pseudocode, a language-independent outline of program logic. Define data structures, handle edge cases, analyze time and memory requirements, and document design patterns and optimization opportunities before implementation.
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Turn specifications and algorithm outlines into a system architecture. Define components, interfaces, data structures, and deployment plans, then document technology choices, security measures, failure handling, and plans for supporting increased usage.
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Organize new features, complex implementations, and architecture changes into the SPARC stages: specification, pseudocode, architecture, refinement, and completion. Define requirements and acceptance criteria, consult existing patterns, and record lessons for future work.
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Turn specifications and designs into working code using test-driven development: write failing tests, implement enough code to pass, then refactor. The workflow also covers error handling, performance improvements, documentation, and coordinated changes across components.
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Turn an approved specification into pseudocode, a plain outline of program logic, and an architecture defining module responsibilities and API inputs and outputs. After user confirmation, proceed with implementation and unit tests based on those designs.
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Review implemented features against their requirements, add missing tests, and check performance constraints. Produce documentation, a table linking requirements to code and tests, and evidence showing whether the feature is ready for deployment.
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Carry out Docupost tasks through Rube MCP, an agent connection to external tools. Discover supported actions, check their required inputs and the service connection, then execute operations according to the specifications returned by tool search.
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