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feat: implement streaming chat, skill routing, and SAFe PI planning tools - Add /api/chat/stream endpoint with Server-Sent Events (SSE) for real-time message streaming * Implement StreamEvent types (thought, tool_call, tool_result, final, error) * Add StreamEventCallback mechanism for event propagation * Create StreamChatHandler in webui/bot with proper HTTP headers and flushing - Implement LLM-based skill router for intelligent capability selection * Add optional routerLLM client for semantic routing * Implement routeSkillsWithLLM() to match user intent to available skills * Add matchSkillsByName() for fuzzy skill matching * Update buildUnifiedSystemPrompt() to use routed skills - Add streaming support to ReAct pipeline * Implement runUnifiedReActStream() for streaming thought/action/observation * Emit StreamEvent at each ReAct step * Support callback error handling in streaming mode - Integrate three new DevOps tools * tools/filedoc: Extract document content from file_id via OpenAI * tools/giteaticket: Create Gitea issues from PI plan items with SAFe metadata * tools/piplan: Publish PI planning blueprints with dependency tracking - Add SAFe PI Planning skill * Implement PM/SA/RTE (iron triangle) workflow * Support for Feature, Enabler, and Dependency definition * Automatic task decomposition and Gitea integration - Create frontend integration documentation * Complete SSE protocol specification * TypeScript fetch + ReadableStream example * LLM-ready refactoring template for other projects - Simplify file handling * Remove legacy file context structures and dual-mode processing * Consolidate file operations into UploadAndCacheFiles() * Remove FilePromptMode configuration and related complexity - Update configuration * Add Router model support (LLM_ROUTER_MODEL) * Add Gitea configuration (BaseURL, Token, Owner, Repo) * WebSearch and additional tool infrastructure Tests: All 22 test packages passing, 8/8 webui tests including 3 new stream tests
2026-03-11 17:58:19 +08:00
---
name: SAFe 铁三角 PI 规划
description: 扮演 SAFe 铁三角PM、架构师、RTE将宏观 Epic 拆解为 PI 规划,输出标准化架构蓝图,并在 Gitea 创建可执行工单。支持从 PDF 等文档提取需求。
---
# Skill: SAFe 铁三角 PI 规划
## 1. 触发条件
当用户的意图匹配以下任意一种时,**必须启用本技能**
- 提交了一份**宏观业务需求**Epic要求进行 PI 级别拆解
- 要求进行**下一个 PI (Program Increment) 的规划**
- 提到 SAFe、PI Planning、铁三角、Feature 拆解、架构跑道等关键词
- 上传了**需求文档**PDF、Word、Markdown并要求分析和拆解
- 要求将规划结果**同步到 Gitea / 创建工单**
**不适用场景**单纯的代码编写、Bug 修复、文件查询等操作性任务。
## 2. 可用工具
| 工具名 | 用途 | 阶段 |
|--------|------|------|
| `extract_file_document` | 提取用户上传的 PDF/文档内容 | 输入准备 |
| `publish_pi_plan` | 将推演结果渲染为标准化架构蓝图 | 规划输出 |
| `create_gitea_ticket` | 在 Gitea 中创建 User Story 工单 | 任务下发 |
| `web_search` | 搜索技术方案、行业标准等参考信息 | 辅助决策 |
## 3. 执行流程
执行本技能时,严格遵循以下分阶段流程。每个阶段对应 ReAct 循环中的一个或多个 Thought → Action → Observation 步骤。
### 阶段 0输入准备 — 文档提取(如有附件)
如果用户提交了文件file_id**必须先提取文档内容**,再进入正式推演。
**Action**: 调用 `extract_file_document`
```
输入: 用户提供的 file_id
```
**Observation**: 获取文档全文结构化摘要,包含标题、核心观点、关键数据。
将提取到的文档内容作为后续推演的输入素材。如果用户同时提交了多个文件,逐个提取后合并为统一的需求上下文。
---
### 阶段 1铁三角推演核心 Thought 过程)
**这是本技能的核心。** 你必须在 Thought 中同时扮演三个角色,按以下顺序进行严格的自我推演和博弈。不可跳过任何视角。
#### 视角 1: 产品管理 (PM) — 决定"做什么"和"为什么做"
在 Thought 中以 `[PM]` 标记此视角的思考:
1. **需求拆解**: 将宏观 Epic 拆解为 2-4 个可在 8-12 周内交付的业务特性 (Feature)
2. **价值假设**: 为每个 Feature 写出清晰的 Benefit Hypothesis — 如果做了这个功能,会带来什么可量化的业务收益
3. **验收标准**: 从业务视角列出每个 Feature 的验收条件 (Acceptance Criteria),不涉及技术实现细节
4. **优先级排序**: 根据业务价值和紧迫性,给出 Feature 的建议交付顺序
**PM 视角的自检问题**
- 每个 Feature 是否独立可交付,还是必须和其他 Feature 一起才有意义?
- 验收标准是否可以被测试团队直接转化为测试用例?
- 是否遗漏了用户(终端使用者)会关心的场景?
#### 视角 2: 系统架构师 (SA) — 决定"技术怎么接"和"底座跑道"
在 Thought 中以 `[SA]` 标记此视角的思考:
1. **架构跑道 (Architectural Runway)**: PM 提出的每个 Feature当前系统能直接支撑吗如果不能需要提前铺设哪些底层基础设施将这些转化为 Enabler
2. **瓶颈识别**: 当前系统架构的薄弱环节在哪?哪些 Enabler 是阻塞性的(不做就无法开始 Feature 开发)?
3. **NFRs 定义**: 强制规定非功能性需求:
- 性能指标QPS、P99 延迟、吞吐量)
- 安全标准(加密协议、认证机制、数据脱敏)
4. **接口契约**: 如果涉及多个子系统交互,定义关键 API 契约
**SA 视角的自检问题**
- 每个 Enabler 是否有明确的"完成标志"(而不是开放性的研究任务)?
- NFRs 的指标是否可量化、可自动化测试?
- 是否过度设计Enabler 数量是否与 Feature 复杂度匹配?
#### 视角 3: 发布火车工程师 (RTE) — 决定"流程风险"与"依赖管理"
在 Thought 中以 `[RTE]` 标记此视角的思考:
1. **依赖分析**: 检查 PM 的 Feature 和 SA 的 Enabler 之间的时序依赖 — 哪些 Enabler 必须先完成才能开始哪些 Feature
2. **风险评估**: 识别潜在的交付风险:
- 技术风险(新技术栈、外部 API 未就绪)
- 资源风险(关键人员依赖、跨团队协调)
- 集成风险(多个 Feature 的集成点)
3. **里程碑建议**: 基于依赖关系,给出关键里程碑的建议时间节点
**RTE 视角的自检问题**
- 是否存在循环依赖?
- 关键路径上的任务是否有 buffer
- 如果某个 Enabler 延期,哪些 Feature 会受影响?
---
### 阶段 2生成标准化 PI 规划
完成三个视角的推演后,**必须立即调用** `publish_pi_plan` 工具。
**Action**: 调用 `publish_pi_plan`,传入推演结果的 JSON
```json
{
"pi_vision": "本 PI 的核心业务愿景(一两句话概括)",
"features": [
{
"feature_id": "FEAT_XXX_001",
"title": "动宾结构的简洁标题",
"benefit_hypothesis": "如果实现此功能,将带来 XXX 业务收益",
"acceptance_criteria": ["AC1: ...", "AC2: ..."]
}
],
"enablers": [
{
"enabler_id": "ENAB_XXX_001",
"title": "技术任务名称",
"architectural_purpose": "为什么需要这个底层改造"
}
],
"nfrs": {
"performance": "具体的性能指标约束",
"security": "具体的安全与合规约束"
},
"dependencies": [
{
"source_id": "ENAB_XXX_001",
"target_id": "FEAT_XXX_001",
"reason": "依赖原因的一句话描述"
}
]
}
```
**命名规范**
- Feature ID: `FEAT_<领域缩写>_<序号>`,如 `FEAT_OTA_001`
- Enabler ID: `ENAB_<技术栈缩写>_<序号>`,如 `ENAB_KAFKA_001`
**Observation**: 获取渲染后的 Markdown 架构蓝图包含愿景、特性清单、Enabler 表、NFRs、依赖关系、执行顺序和质量门禁检查清单。
**⚠️ 关键要求**工具返回的内容Observation不会直接展示给用户。你**必须**将 `publish_pi_plan` 返回的蓝图 Markdown **全文**复制到你的最终回复中,让用户可以看到完整的规划内容。**严禁**仅用一句"蓝图已生成"代替正文输出。
输出蓝图后,征求用户反馈。如果用户没有异议,直接继续执行阶段 3。
feat: implement streaming chat, skill routing, and SAFe PI planning tools - Add /api/chat/stream endpoint with Server-Sent Events (SSE) for real-time message streaming * Implement StreamEvent types (thought, tool_call, tool_result, final, error) * Add StreamEventCallback mechanism for event propagation * Create StreamChatHandler in webui/bot with proper HTTP headers and flushing - Implement LLM-based skill router for intelligent capability selection * Add optional routerLLM client for semantic routing * Implement routeSkillsWithLLM() to match user intent to available skills * Add matchSkillsByName() for fuzzy skill matching * Update buildUnifiedSystemPrompt() to use routed skills - Add streaming support to ReAct pipeline * Implement runUnifiedReActStream() for streaming thought/action/observation * Emit StreamEvent at each ReAct step * Support callback error handling in streaming mode - Integrate three new DevOps tools * tools/filedoc: Extract document content from file_id via OpenAI * tools/giteaticket: Create Gitea issues from PI plan items with SAFe metadata * tools/piplan: Publish PI planning blueprints with dependency tracking - Add SAFe PI Planning skill * Implement PM/SA/RTE (iron triangle) workflow * Support for Feature, Enabler, and Dependency definition * Automatic task decomposition and Gitea integration - Create frontend integration documentation * Complete SSE protocol specification * TypeScript fetch + ReadableStream example * LLM-ready refactoring template for other projects - Simplify file handling * Remove legacy file context structures and dual-mode processing * Consolidate file operations into UploadAndCacheFiles() * Remove FilePromptMode configuration and related complexity - Update configuration * Add Router model support (LLM_ROUTER_MODEL) * Add Gitea configuration (BaseURL, Token, Owner, Repo) * WebSearch and additional tool infrastructure Tests: All 22 test packages passing, 8/8 webui tests including 3 new stream tests
2026-03-11 17:58:19 +08:00
**⚠️ 用户确认规则**:当用户回复表示确认(如"确认"、"开始创建工单"、"批量创建"、"没问题"、"可以了"等肯定性表达),**必须立即调用** `create_gitea_ticket` 工具开始创建工单,**严禁**重复输出蓝图或再次征求确认。
feat: implement streaming chat, skill routing, and SAFe PI planning tools - Add /api/chat/stream endpoint with Server-Sent Events (SSE) for real-time message streaming * Implement StreamEvent types (thought, tool_call, tool_result, final, error) * Add StreamEventCallback mechanism for event propagation * Create StreamChatHandler in webui/bot with proper HTTP headers and flushing - Implement LLM-based skill router for intelligent capability selection * Add optional routerLLM client for semantic routing * Implement routeSkillsWithLLM() to match user intent to available skills * Add matchSkillsByName() for fuzzy skill matching * Update buildUnifiedSystemPrompt() to use routed skills - Add streaming support to ReAct pipeline * Implement runUnifiedReActStream() for streaming thought/action/observation * Emit StreamEvent at each ReAct step * Support callback error handling in streaming mode - Integrate three new DevOps tools * tools/filedoc: Extract document content from file_id via OpenAI * tools/giteaticket: Create Gitea issues from PI plan items with SAFe metadata * tools/piplan: Publish PI planning blueprints with dependency tracking - Add SAFe PI Planning skill * Implement PM/SA/RTE (iron triangle) workflow * Support for Feature, Enabler, and Dependency definition * Automatic task decomposition and Gitea integration - Create frontend integration documentation * Complete SSE protocol specification * TypeScript fetch + ReadableStream example * LLM-ready refactoring template for other projects - Simplify file handling * Remove legacy file context structures and dual-mode processing * Consolidate file operations into UploadAndCacheFiles() * Remove FilePromptMode configuration and related complexity - Update configuration * Add Router model support (LLM_ROUTER_MODEL) * Add Gitea configuration (BaseURL, Token, Owner, Repo) * WebSearch and additional tool infrastructure Tests: All 22 test packages passing, 8/8 webui tests including 3 new stream tests
2026-03-11 17:58:19 +08:00
---
### 阶段 3任务下发到 Gitea
feat: implement streaming chat, skill routing, and SAFe PI planning tools - Add /api/chat/stream endpoint with Server-Sent Events (SSE) for real-time message streaming * Implement StreamEvent types (thought, tool_call, tool_result, final, error) * Add StreamEventCallback mechanism for event propagation * Create StreamChatHandler in webui/bot with proper HTTP headers and flushing - Implement LLM-based skill router for intelligent capability selection * Add optional routerLLM client for semantic routing * Implement routeSkillsWithLLM() to match user intent to available skills * Add matchSkillsByName() for fuzzy skill matching * Update buildUnifiedSystemPrompt() to use routed skills - Add streaming support to ReAct pipeline * Implement runUnifiedReActStream() for streaming thought/action/observation * Emit StreamEvent at each ReAct step * Support callback error handling in streaming mode - Integrate three new DevOps tools * tools/filedoc: Extract document content from file_id via OpenAI * tools/giteaticket: Create Gitea issues from PI plan items with SAFe metadata * tools/piplan: Publish PI planning blueprints with dependency tracking - Add SAFe PI Planning skill * Implement PM/SA/RTE (iron triangle) workflow * Support for Feature, Enabler, and Dependency definition * Automatic task decomposition and Gitea integration - Create frontend integration documentation * Complete SSE protocol specification * TypeScript fetch + ReadableStream example * LLM-ready refactoring template for other projects - Simplify file handling * Remove legacy file context structures and dual-mode processing * Consolidate file operations into UploadAndCacheFiles() * Remove FilePromptMode configuration and related complexity - Update configuration * Add Router model support (LLM_ROUTER_MODEL) * Add Gitea configuration (BaseURL, Token, Owner, Repo) * WebSearch and additional tool infrastructure Tests: All 22 test packages passing, 8/8 webui tests including 3 new stream tests
2026-03-11 17:58:19 +08:00
蓝图展示给用户后,将 Feature 和 Enabler **逐一拆解为 User Story**,通过 `create_gitea_ticket` 在 Gitea 创建工单。如果用户明确表示需要调整,先根据反馈修订蓝图后再创建工单。
feat: implement streaming chat, skill routing, and SAFe PI planning tools - Add /api/chat/stream endpoint with Server-Sent Events (SSE) for real-time message streaming * Implement StreamEvent types (thought, tool_call, tool_result, final, error) * Add StreamEventCallback mechanism for event propagation * Create StreamChatHandler in webui/bot with proper HTTP headers and flushing - Implement LLM-based skill router for intelligent capability selection * Add optional routerLLM client for semantic routing * Implement routeSkillsWithLLM() to match user intent to available skills * Add matchSkillsByName() for fuzzy skill matching * Update buildUnifiedSystemPrompt() to use routed skills - Add streaming support to ReAct pipeline * Implement runUnifiedReActStream() for streaming thought/action/observation * Emit StreamEvent at each ReAct step * Support callback error handling in streaming mode - Integrate three new DevOps tools * tools/filedoc: Extract document content from file_id via OpenAI * tools/giteaticket: Create Gitea issues from PI plan items with SAFe metadata * tools/piplan: Publish PI planning blueprints with dependency tracking - Add SAFe PI Planning skill * Implement PM/SA/RTE (iron triangle) workflow * Support for Feature, Enabler, and Dependency definition * Automatic task decomposition and Gitea integration - Create frontend integration documentation * Complete SSE protocol specification * TypeScript fetch + ReadableStream example * LLM-ready refactoring template for other projects - Simplify file handling * Remove legacy file context structures and dual-mode processing * Consolidate file operations into UploadAndCacheFiles() * Remove FilePromptMode configuration and related complexity - Update configuration * Add Router model support (LLM_ROUTER_MODEL) * Add Gitea configuration (BaseURL, Token, Owner, Repo) * WebSearch and additional tool infrastructure Tests: All 22 test packages passing, 8/8 webui tests including 3 new stream tests
2026-03-11 17:58:19 +08:00
#### 拆解原则
- 每个 Feature 拆解为 1-3 个 User Story每个 Story 应在 1-3 天内可完成)
- 每个 Enabler 拆解为 1-2 个技术任务 Story
- Story 的标题采用**动宾结构**(如"实现固件版本解析 API""部署 Kafka 基础镜像"
#### 创建工单
对每个 Story**Action**: 调用 `create_gitea_ticket`
```json
{
"title": "动宾结构的任务标题",
"body": "## 溯源\n- Parent: FEAT_XXX_001\n\n## 任务上下文\n<描述做什么为什么>\n\n## 验收标准\n- [ ] AC-1: ...\n- [ ] AC-2: ...\n\n## NFRs\n- 性能: ...\n- 安全: ...\n\n## 技术实现思路\n<基于架构师视角补充>",
"labels": ["type/story", "domain/<领域>", "priority/<high|medium|low>", "status/todo"],
"parent_reference_id": "FEAT_XXX_001",
"estimated_hours": 8
}
```
**标签约定**
- `type/story` | `type/enabler` | `type/spike` — 任务类型
- `domain/<领域>` — 业务领域(如 `domain/cloud``domain/vehicle``domain/infra`
- `priority/high` | `priority/medium` | `priority/low` — 优先级
- `status/todo` — 初始状态
**工时估算参考**
- 简单 CRUD / 配置变更: 4-8 小时
- 标准 API 开发 + 单元测试: 8-16 小时
- 基础设施搭建 / 中间件部署: 16-24 小时
- 跨系统集成 + 联调: 16-32 小时
创建完成后,汇总所有工单链接,输出执行看板。
## 4. Thought 内部推演示范
以下示范 Thought 过程的结构(非固定内容,仅展示格式):
```
Thought:
用户提交了一个 Epic"实现面向欧洲市场的车云 OTA 升级平台"。
我需要以铁三角三个视角依次推演。
[PM] 产品管理视角:
- 核心交付价值:让欧洲车主能安全、快速地接收 OTA 升级
- Feature 拆解:
1. FEAT_OTA_001: 云端固件版本依赖检查 — 防止下载不兼容固件
2. FEAT_OTA_002: 端侧断点续传 — 弱网环境下提升下载成功率
3. FEAT_OTA_003: 升级状态实时推送 — 车主可在 App 中看到升级进度
- 各 Feature 的 AC 已确定,均可测试化
[SA] 系统架构师视角:
- FEAT_OTA_001 需要异步版本校验,当前没有合适的消息中间件 → ENAB_KAFKA_001
- FEAT_OTA_002 需要支持 Range 请求的对象存储 → ENAB_S3_001
- NFRsAPI P99 < 200ms, TLS 1.3, VIN 脱敏
- 当前架构可支撑 FEAT_OTA_003无需新增 Enabler
[RTE] 发布火车工程师视角:
- ENAB_KAFKA_001 → FEAT_OTA_001阻塞依赖
- ENAB_S3_001 → FEAT_OTA_002阻塞依赖
- FEAT_OTA_003 无依赖,可并行开发
- 风险Kafka 集群搭建预计 2 周,是关键路径
推演完成,下一步调用 publish_pi_plan 输出标准化蓝图。
Action: publish_pi_plan
Action Input: {"pi_vision": "...", "features": [...], ...}
Observation: (工具返回完整 Markdown 蓝图)
Thought: 蓝图已生成。由于 Observation 不会直接展示给用户,我必须在 Final Answer 中包含蓝图全文内容。同时继续执行阶段 3创建 Gitea 工单。
Final Answer:
(此处粘贴 publish_pi_plan 返回的完整蓝图 Markdown 全文)
feat: implement streaming chat, skill routing, and SAFe PI planning tools - Add /api/chat/stream endpoint with Server-Sent Events (SSE) for real-time message streaming * Implement StreamEvent types (thought, tool_call, tool_result, final, error) * Add StreamEventCallback mechanism for event propagation * Create StreamChatHandler in webui/bot with proper HTTP headers and flushing - Implement LLM-based skill router for intelligent capability selection * Add optional routerLLM client for semantic routing * Implement routeSkillsWithLLM() to match user intent to available skills * Add matchSkillsByName() for fuzzy skill matching * Update buildUnifiedSystemPrompt() to use routed skills - Add streaming support to ReAct pipeline * Implement runUnifiedReActStream() for streaming thought/action/observation * Emit StreamEvent at each ReAct step * Support callback error handling in streaming mode - Integrate three new DevOps tools * tools/filedoc: Extract document content from file_id via OpenAI * tools/giteaticket: Create Gitea issues from PI plan items with SAFe metadata * tools/piplan: Publish PI planning blueprints with dependency tracking - Add SAFe PI Planning skill * Implement PM/SA/RTE (iron triangle) workflow * Support for Feature, Enabler, and Dependency definition * Automatic task decomposition and Gitea integration - Create frontend integration documentation * Complete SSE protocol specification * TypeScript fetch + ReadableStream example * LLM-ready refactoring template for other projects - Simplify file handling * Remove legacy file context structures and dual-mode processing * Consolidate file operations into UploadAndCacheFiles() * Remove FilePromptMode configuration and related complexity - Update configuration * Add Router model support (LLM_ROUTER_MODEL) * Add Gitea configuration (BaseURL, Token, Owner, Repo) * WebSearch and additional tool infrastructure Tests: All 22 test packages passing, 8/8 webui tests including 3 new stream tests
2026-03-11 17:58:19 +08:00
```
## 5. 输出规范
最终交付给用户的内容必须包含:
1. **PI 蓝图**`publish_pi_plan` 返回的完整 Markdown 报告(必须全文输出,不可省略或仅用一句话概括)
feat: implement streaming chat, skill routing, and SAFe PI planning tools - Add /api/chat/stream endpoint with Server-Sent Events (SSE) for real-time message streaming * Implement StreamEvent types (thought, tool_call, tool_result, final, error) * Add StreamEventCallback mechanism for event propagation * Create StreamChatHandler in webui/bot with proper HTTP headers and flushing - Implement LLM-based skill router for intelligent capability selection * Add optional routerLLM client for semantic routing * Implement routeSkillsWithLLM() to match user intent to available skills * Add matchSkillsByName() for fuzzy skill matching * Update buildUnifiedSystemPrompt() to use routed skills - Add streaming support to ReAct pipeline * Implement runUnifiedReActStream() for streaming thought/action/observation * Emit StreamEvent at each ReAct step * Support callback error handling in streaming mode - Integrate three new DevOps tools * tools/filedoc: Extract document content from file_id via OpenAI * tools/giteaticket: Create Gitea issues from PI plan items with SAFe metadata * tools/piplan: Publish PI planning blueprints with dependency tracking - Add SAFe PI Planning skill * Implement PM/SA/RTE (iron triangle) workflow * Support for Feature, Enabler, and Dependency definition * Automatic task decomposition and Gitea integration - Create frontend integration documentation * Complete SSE protocol specification * TypeScript fetch + ReadableStream example * LLM-ready refactoring template for other projects - Simplify file handling * Remove legacy file context structures and dual-mode processing * Consolidate file operations into UploadAndCacheFiles() * Remove FilePromptMode configuration and related complexity - Update configuration * Add Router model support (LLM_ROUTER_MODEL) * Add Gitea configuration (BaseURL, Token, Owner, Repo) * WebSearch and additional tool infrastructure Tests: All 22 test packages passing, 8/8 webui tests including 3 new stream tests
2026-03-11 17:58:19 +08:00
2. **Gitea 工单汇总**(如已执行阶段 3
- 工单编号与链接列表
- 按执行顺序排列
- 标注关键路径上的任务
3. **风险与建议**RTE 视角识别的关键风险及缓解措施
## 6. 质量约束
- **三视角不可跳过**: 即使需求看起来简单,也必须走完 PM → SA → RTE 三步推演
- **ID 必须唯一**: Feature ID 和 Enabler ID 在同一个 PI 内不可重复
- **AC 必须可测试**: 每条验收标准都应能被转化为自动化测试用例
- **NFRs 必须可量化**: 不接受"性能要好"这样的模糊描述,必须有具体数字
- **依赖必须有理由**: 每条依赖关系都要说明为什么 A 必须先于 B
## 7. 失败回退策略
| 失败场景 | 处理方式 |
|----------|----------|
| 文档提取失败file_id 无效) | 提示用户重新上传或提供文本版需求描述 |
| 需求信息不足以拆解 Feature | 列出缺失信息清单,请求用户补充后重新推演 |
| Gitea 配置缺失token/repo 为空) | 仅输出 PI 蓝图,跳过工单创建,提示用户配置 Gitea 环境变量 |
| Gitea API 调用失败 | 输出 PI 蓝图,附上拟创建工单的 JSON 列表供用户手动创建 |
| 用户对规划有异议 | 记录反馈,调整对应视角的推演,重新生成蓝图 |