원클릭으로
spec-context-resume
恢复功能的开发上下文。 加载最近会话完整内容 + 历史摘要。
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
메뉴
恢复功能的开发上下文。 加载最近会话完整内容 + 历史摘要。
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
保存当前窗口的所有对话记录。保存后建议新开窗口 Resume。 触发时机:用户请求保存、重要节点、长对话。
Extract and persist project knowledge from spec-workflow conversations. Scans user-AI dialogues for coding conventions, architecture decisions, and project patterns, then writes them back to steering documents or conventions directory. Use when (1) a spec-workflow phase completes and new learnings are detected, (2) the user wants to update project conventions, (3) the user says "remember" to persist a specific convention, or (4) the user wants to review and consolidate knowledge from recent features. Triggers include "spec-reflect", "learn conventions", "update conventions", "remember:", "学习规范", "更新规范", "总结回写", "记住这个约定".
Perform comprehensive code review for features developed through the spec-workflow process. Use when all implementation tasks are completed and the user wants to review code quality before generating unit tests or merging. Triggers include "code review for {feature}", "review code", "检查代码", "代码审查", "spec review", or when spec-run's All Tasks Complete Flow offers the code review option. Also use when the user asks to fix review issues, re-review after fixes, or wants to understand the quality of their spec-workflow implementation. This skill integrates with spec-workflow as a post-implementation quality gate — think of it as having a senior engineer review your feature branch before it goes anywhere.
This skill provides a spec-driven development workflow for systematic feature implementation with validation at each stage. Use when the user wants to (1) initialize a project with steering documents, (2) create feature specifications (requirements, design, tasks), (3) validate specification documents (requirements, design, tasks), (4) execute implementation tasks, (5) generate unit tests for a completed feature, (6) review code for a completed feature, (7) create/analyze/fix/verify bugs, (8) asks about spec-driven development workflow, (9) extract and persist project knowledge from conversations, (10) save/checkpoint conversation context for a feature, or (11) resume/restore conversation context for a feature. Triggers include "create spec", "create requirements/design/tasks", "initialize project", "initialize module", "validate requirements/design/tasks", "execute task", "generate tests", "create unit tests", "code review", "review code", "检查代码", "代码审查", "spec-reflect", "learn conventions", "update conventi
| name | spec-context-resume |
| description | 恢复功能的开发上下文。 加载最近会话完整内容 + 历史摘要。 |
从用户请求识别功能名称:
确认清单文件存在(使用工作空间相对路径):
<工作空间>/.claude/spec-workflow/specs/{功能名}/.context/manifest.json
⚠️ 路径规则
- 必须使用相对于工作空间的路径,不要使用绝对路径
- 每个用户的工作空间目录可能不同,但相对路径结构一致
- 示例:如果功能名是
block-user-personal-chat,则路径为:.claude/spec-workflow/specs/block-user-personal-chat/.context/manifest.json
manifest = read_json(f".claude/spec-workflow/specs/{功能名}/.context/manifest.json")
info = {
"feature": manifest["specId"],
"total_turns": manifest["turnWatermark"]["lastSessionEndTurn"],
"last_chunked": manifest["turnWatermark"]["lastChunkedTurn"],
"chunks": manifest.get("semanticChunks", []),
"sessions": manifest.get("recentSessions", [])
}
# 找最近的会话
recent = sorted(manifest["recentSessions"],
key=lambda s: s["globalRange"][1],
reverse=True)[0]
session_dir = f".claude/spec-workflow/specs/{功能名}/.context/conversations/sessions/{recent['sessionId']}"
metadata = read_json(f"{session_dir}/metadata.json")
# 加载对话文件(最多 12 轮)
turn_files = sorted(glob(f"{session_dir}/turn-*.md"))[-12:]
for f in turn_files:
content = read_file(f)
# 加入上下文
for chunk in manifest.get("semanticChunks", []):
chunk_path = f".claude/spec-workflow/specs/{功能名}/.context/conversations/{chunk['file']}"
chunk_content = read_file(chunk_path)
# 加入上下文
docs = ["requirements.md", "design.md", "tasks.md"]
for doc in docs:
path = f".claude/spec-workflow/specs/{功能名}/{doc}"
if exists(path):
# 读取前 30 行作为预览
preview = read_lines(path, 1, 30)
# 恢复: {功能名}
## 📊 状态概览
| 项目 | 值 |
|------|-----|
| 功能 | block-user-personal-chat |
| 总对话轮数 | 30 |
| 当前阶段 | 设计 |
| 最近会话 | session-003 (第23-30轮) |
---
## 📝 最近对话 (会话-003)
### 第25轮
**用户**: API 的错误码怎么设计?
**助手**: 建议使用以下错误码结构:
```json
{
"code": "BLOCK_001",
"message": "用户已被屏蔽"
}
...
用户: 加个批量接口
助手: 好的,添加批量屏蔽接口:
POST /api/v1/block/batch
...
需求分析阶段,确定了用户屏蔽功能的基本需求。
设计阶段,完成了 API 和数据库设计。
| 文档 | 状态 |
|---|---|
| requirements.md | ✅ 3 个用户故事 |
| design.md | ✅ API + 数据库设计 |
| tasks.md | ✅ 12 个任务,完成 8 个 |
上下文已加载,请继续之前的工作。
如需查看完整文档,请说:
---
## 按需加载
### 查看文档
**用户**:"查看 design.md"
**AI**:读取并展示完整文档内容
### 查看特定摘要
**用户**:"查看摘要-001详情"
**AI**:读取并展示摘要完整内容
---
## 目录结构
<工作空间>/ └── .claude/ └── spec-workflow/ └── specs/ └── {功能名}/ ├── requirements.md ← 文档索引 ├── design.md ├── tasks.md └── .context/ ├── manifest.json ← 首先读取 └── conversations/ ├── semantic-chunks/ │ ├── chunk-001.md ← 加载摘要 │ └── chunk-002.md └── sessions/ └── session-003/ ← 完整加载 ├── metadata.json └── turn-*.md
> 📌 **注意**:所有路径都是相对于工作空间根目录,确保跨环境一致性。
---
## 错误处理
### 清单文件不存在
```markdown
❌ **无法恢复**
功能 `{名称}` 没有保存的上下文。
请检查:
1. 功能名称是否正确
2. 是否执行过保存
⚠️ **部分加载**
部分文件无法读取,已加载可用内容。
建议重新执行保存。