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从想法到论文的全自主研究管道，6阶段，含HITL，输出到Obsidian\n\nTags: latest:1.0.3\n\nVersion history:\n\nv1.0.3 | 2026-04-24T04:15:33.588Z | auto\n\n- Version bump from 1.0.2 to 1.0.3.\n- No changes to files or functionality in this release.\n- Documentation and skill description remain unchanged.\n\nv1.0.2 | 2026-04-23T03:21:49.150Z | user\n\nv1.0.2 把本地工作态同步到 clawhub（之前本地版本号落后于 clawhub）\n\nv1.0.1 | 2026-04-21T17:08:30.196Z | auto\n\n- Added _meta.json file for skill metadata.\n- Updated SKILL.md to use YAML front matter for structured metadata.\n- No changes to the research pipeline logic or user-facing features.\n\nv1.0.0 | 2026-04-21T17:01:33.714Z | auto\n\nInitial release of huo15-research-pipeline, an end-to-end automated research workflow inspired by AutoResearchClaw.\n\n- Automates the full research process from idea to paper, including scope definition, literature discovery, synthesis, experiment design, analysis, and paper writing.\n- Human-in-the-loop: user confirms outputs at each phase before proceeding.\n- All artifacts saved in organized markdown files, compatible with Obsidian.\n- Usable via CLI with structured output directory per research topic.\n- Supports resuming from interruption and produces academic-standard papers.\n\nArchive index:\n\nArchive v1.0.3: 9 files, 12279 bytes\n\nFiles: _meta.json (142b), scripts/research.sh (13021b), scripts/templates/phase_a_scope.sh (911b), scripts/templates/phase_b_discovery.sh (1100b), scripts/templates/phase_c_synthesis.sh (1226b), scripts/templates/phase_d_experiment.sh (1338b), scripts/templates/phase_g_write.sh (1835b), skill-card.md (2218b), SKILL.md (4623b)\n\nFile v1.0.3:SKILL.md\n\n---\nname: huo15-research-pipeline\nversion: 1.0.2\naliases:\n  - 火一五研究管道\n  - 火一五论文管道\n  - 自动研究\ndescription: 从想法到论文的全自主研究管道，6阶段，含HITL，输出到Obsidian\n---\n# huo15-research-pipeline\n\n> 从想法到论文的全自主研究管道，灵感来自 AutoResearchClaw\n\n## 元信息\n\n- **version**: 1.0.0\n- **trigger**: 研究管道、research pipeline、自动研究、想法到论文、研究 [课题]\n- **author**: huo15\n- **compatibility**: OpenClaw >= 1.0\n\n## 功能概述\n\n将一个研究课题全自动推进至论文产出，涵盖范围定义、文献发现、知识综合、实验设计、结果分析与论文撰写。全程人类在环（HITL），每个 Phase 完成后等待用户确认。\n\n## 核心流程\n\n```\n用户: \"研究 [课题]\"\n         │\n         ▼\n  ┌─────────────────┐\n  │  Phase A: 范围定义  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase B: 文献发现  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase C: 知识综合  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase D: 实验设计  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase E: 结果分析  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase F: 论文撰写  │  → 完成\n  └────────┬────────┘\n           ▼\n      输出到 Obsidian\n```\n\n## Phase 详细说明\n\n### Phase A: 研究范围定义\n\n定义研究问题、目标、范围边界和成功标准。\n\n**输出：**\n- 研究问题（1-3 个核心问题）\n- 研究目标（ SMART 格式）\n- 范围边界（ in-scope / out-of-scope）\n- 成功标准\n\n### Phase B: 文献发现与筛选\n\n搜索相关论文、博客、技术报告，筛选高质量来源。\n\n**输出：**\n- 关键词列表\n- 筛选出的文献列表（含标题、摘要、链接）\n- 文献质量评分\n\n### Phase C: 知识综合与假设生成\n\n整合文献发现，生成假设或研究问题。\n\n**输出：**\n- 知识图谱摘要\n- 核心发现列表\n- 假设 / 待验证命题\n\n### Phase D: 实验设计与执行\n\n设计验证假设的实验方案，包括数据、方法和评估指标。\n\n**输出：**\n- 实验设计方案\n- 数据需求\n- 评估指标\n\n### Phase E: 结果分析\n\n分析实验结果，生成洞察。\n\n**输出：**\n- 结果摘要\n- 统计显著性（如适用）\n- 洞察列表\n\n### Phase F: 论文撰写\n\n按学术论文结构输出完整内容。\n\n**输出：**\n- 标题 + 摘要\n- 引言\n- 相关工作\n- 方法\n- 结果\n- 讨论\n- 结论\n- 参考文献\n\n## 使用方式\n\n```\n用户: 研究 大语言模型在代码补全任务中的性能评估\n```\n\n或直接说：\n\n```\n用户: 自动研究 基于强化学习的机器人抓取策略\n```\n\n## 输出位置\n\n所有研究产物保存至：\n\n```\n$HOME/.openclaw/agents/main/agent/kb/raw/research-{课题名}-{日期}/\n```\n\n结构：\n```\nresearch-{课题}-{日期}/\n├── 00_scope.md        # Phase A 输出\n├── 01_discovery.md    # Phase B 输出\n├── 02_synthesis.md    # Phase C 输出\n├── 03_experiment.md   # Phase D 输出\n├── 04_analysis.md     # Phase E 输出\n├── 05_paper.md        # Phase F 输出（完整论文）\n└── log.txt            # 执行日志\n```\n\n## 人类在环（HITL）\n\n每个 Phase 完成后，脚本会：\n1. 显示该阶段产出摘要\n2. 询问用户：`继续下一步 / 调整参数 / 终止`\n3. 等待用户输入后执行下一阶段\n\n## 调用示例\n\n```bash\ncd ~/.openclaw/workspace/skills/huo15-research-pipeline\n./scripts/research.sh \"大语言模型在代码补全任务中的性能评估\"\n```\n\n## 依赖\n\n- `openclaw` CLI（用于 LLM 调用）\n- `curl`（用于 Web 搜索）\n- `jq`（用于 JSON 解析）\n- `obsidian-cli`（可选，用于直接写入 Obsidian）\n\n## 注意事项\n\n- 研究过程可能耗时较长，建议在空闲时运行\n- 每个 Phase 的产出都会保存，中断后可从断点继续\n- 论文撰写 Phase 会尽量保持学术规范，可直接提交或进一步编辑\n\nFile v1.0.3:_meta.json\n\n{\n  \"ownerId\": \"kn7byevkn40d6z4p7ghdb097z983tj33\",\n  \"slug\": \"huo15-research-pipeline\",\n  \"version\": \"1.0.3\",\n  \"publishedAt\": 1777004133588\n}\n\nFile v1.0.3:skill-card.md\n\n## Description:\n\nA Chinese-language research pipeline that moves a topic through scope definition, literature discovery, synthesis, experiment design, analysis, and paper drafting with human confirmation between phases.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[zhaobod1](https://clawhub.ai/user/zhaobod1)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers, researchers, and OpenClaw users use this skill to turn an initial research topic into staged Markdown research artifacts and a draft academic paper. It is intended for workflows where a human reviews each phase before the next phase proceeds.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Research topics, prompts, and generated notes may be sent to the configured OpenClaw LLM provider.\n\nMitigation: Use only environments approved for the research data, and avoid confidential or proprietary topics unless that provider and environment are authorized.\n\nRisk: Generated research outputs are persisted under the OpenClaw knowledge-base path.\n\nMitigation: Review output locations, access controls, and retention before running the pipeline on sensitive topics.\n\nRisk: Obsidian integration is optional and may not automatically sync results in every environment.\n\nMitigation: Treat Obsidian export as a manual follow-up unless the local Obsidian command is installed and tested.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/zhaobod1/skills/huo15-research-pipeline)\n- [Publisher profile](https://clawhub.ai/user/zhaobod1)\n\n## Skill Output:\n\n**Output Type(s):** [text, markdown, shell commands, guidance]\n\n**Output Format:** [Markdown files and terminal prompts]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Creates staged research notes, a paper draft, and a log under the configured OpenClaw knowledge-base path.]\n\n## Skill Version(s):\n\n1.0.3 (source: server release metadata)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nArchive v1.0.2: 8 files, 11064 bytes\n\nFiles: _meta.json (142b), scripts/research.sh (13021b), scripts/templates/phase_a_scope.sh (911b), scripts/templates/phase_b_discovery.sh (1100b), scripts/templates/phase_c_synthesis.sh (1226b), scripts/templates/phase_d_experiment.sh (1338b), scripts/templates/phase_g_write.sh (1835b), SKILL.md (4623b)\n\nFile v1.0.2:SKILL.md\n\n---\nname: huo15-research-pipeline\nversion: 1.0.2\naliases:\n  - 火一五研究管道\n  - 火一五论文管道\n  - 自动研究\ndescription: 从想法到论文的全自主研究管道，6阶段，含HITL，输出到Obsidian\n---\n# huo15-research-pipeline\n\n> 从想法到论文的全自主研究管道，灵感来自 AutoResearchClaw\n\n## 元信息\n\n- **version**: 1.0.0\n- **trigger**: 研究管道、research pipeline、自动研究、想法到论文、研究 [课题]\n- **author**: huo15\n- **compatibility**: OpenClaw >= 1.0\n\n## 功能概述\n\n将一个研究课题全自动推进至论文产出，涵盖范围定义、文献发现、知识综合、实验设计、结果分析与论文撰写。全程人类在环（HITL），每个 Phase 完成后等待用户确认。\n\n## 核心流程\n\n```\n用户: \"研究 [课题]\"\n         │\n         ▼\n  ┌─────────────────┐\n  │  Phase A: 范围定义  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase B: 文献发现  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase C: 知识综合  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase D: 实验设计  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase E: 结果分析  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase F: 论文撰写  │  → 完成\n  └────────┬────────┘\n           ▼\n      输出到 Obsidian\n```\n\n## Phase 详细说明\n\n### Phase A: 研究范围定义\n\n定义研究问题、目标、范围边界和成功标准。\n\n**输出：**\n- 研究问题（1-3 个核心问题）\n- 研究目标（ SMART 格式）\n- 范围边界（ in-scope / out-of-scope）\n- 成功标准\n\n### Phase B: 文献发现与筛选\n\n搜索相关论文、博客、技术报告，筛选高质量来源。\n\n**输出：**\n- 关键词列表\n- 筛选出的文献列表（含标题、摘要、链接）\n- 文献质量评分\n\n### Phase C: 知识综合与假设生成\n\n整合文献发现，生成假设或研究问题。\n\n**输出：**\n- 知识图谱摘要\n- 核心发现列表\n- 假设 / 待验证命题\n\n### Phase D: 实验设计与执行\n\n设计验证假设的实验方案，包括数据、方法和评估指标。\n\n**输出：**\n- 实验设计方案\n- 数据需求\n- 评估指标\n\n### Phase E: 结果分析\n\n分析实验结果，生成洞察。\n\n**输出：**\n- 结果摘要\n- 统计显著性（如适用）\n- 洞察列表\n\n### Phase F: 论文撰写\n\n按学术论文结构输出完整内容。\n\n**输出：**\n- 标题 + 摘要\n- 引言\n- 相关工作\n- 方法\n- 结果\n- 讨论\n- 结论\n- 参考文献\n\n## 使用方式\n\n```\n用户: 研究 大语言模型在代码补全任务中的性能评估\n```\n\n或直接说：\n\n```\n用户: 自动研究 基于强化学习的机器人抓取策略\n```\n\n## 输出位置\n\n所有研究产物保存至：\n\n```\n$HOME/.openclaw/agents/main/agent/kb/raw/research-{课题名}-{日期}/\n```\n\n结构：\n```\nresearch-{课题}-{日期}/\n├── 00_scope.md        # Phase A 输出\n├── 01_discovery.md    # Phase B 输出\n├── 02_synthesis.md    # Phase C 输出\n├── 03_experiment.md   # Phase D 输出\n├── 04_analysis.md     # Phase E 输出\n├── 05_paper.md        # Phase F 输出（完整论文）\n└── log.txt            # 执行日志\n```\n\n## 人类在环（HITL）\n\n每个 Phase 完成后，脚本会：\n1. 显示该阶段产出摘要\n2. 询问用户：`继续下一步 / 调整参数 / 终止`\n3. 等待用户输入后执行下一阶段\n\n## 调用示例\n\n```bash\ncd ~/.openclaw/workspace/skills/huo15-research-pipeline\n./scripts/research.sh \"大语言模型在代码补全任务中的性能评估\"\n```\n\n## 依赖\n\n- `openclaw` CLI（用于 LLM 调用）\n- `curl`（用于 Web 搜索）\n- `jq`（用于 JSON 解析）\n- `obsidian-cli`（可选，用于直接写入 Obsidian）\n\n## 注意事项\n\n- 研究过程可能耗时较长，建议在空闲时运行\n- 每个 Phase 的产出都会保存，中断后可从断点继续\n- 论文撰写 Phase 会尽量保持学术规范，可直接提交或进一步编辑\n\nFile v1.0.2:_meta.json\n\n{\n  \"ownerId\": \"kn7byevkn40d6z4p7ghdb097z983tj33\",\n  \"slug\": \"huo15-research-pipeline\",\n  \"version\": \"1.0.2\",\n  \"publishedAt\": 1776914509150\n}\n\nArchive v1.0.1: 8 files, 11063 bytes\n\nFiles: _meta.json (142b), scripts/research.sh (13021b), scripts/templates/phase_a_scope.sh (911b), scripts/templates/phase_b_discovery.sh (1100b), scripts/templates/phase_c_synthesis.sh (1226b), scripts/templates/phase_d_experiment.sh (1338b), scripts/templates/phase_g_write.sh (1835b), SKILL.md (4623b)\n\nFile v1.0.1:SKILL.md\n\n---\nname: huo15-research-pipeline\nversion: 1.0.0\naliases:\n  - 火一五研究管道\n  - 火一五论文管道\n  - 自动研究\ndescription: 从想法到论文的全自主研究管道，6阶段，含HITL，输出到Obsidian\n---\n# huo15-research-pipeline\n\n> 从想法到论文的全自主研究管道，灵感来自 AutoResearchClaw\n\n## 元信息\n\n- **version**: 1.0.0\n- **trigger**: 研究管道、research pipeline、自动研究、想法到论文、研究 [课题]\n- **author**: huo15\n- **compatibility**: OpenClaw >= 1.0\n\n## 功能概述\n\n将一个研究课题全自动推进至论文产出，涵盖范围定义、文献发现、知识综合、实验设计、结果分析与论文撰写。全程人类在环（HITL），每个 Phase 完成后等待用户确认。\n\n## 核心流程\n\n```\n用户: \"研究 [课题]\"\n         │\n         ▼\n  ┌─────────────────┐\n  │  Phase A: 范围定义  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase B: 文献发现  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase C: 知识综合  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase D: 实验设计  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase E: 结果分析  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase F: 论文撰写  │  → 完成\n  └────────┬────────┘\n           ▼\n      输出到 Obsidian\n```\n\n## Phase 详细说明\n\n### Phase A: 研究范围定义\n\n定义研究问题、目标、范围边界和成功标准。\n\n**输出：**\n- 研究问题（1-3 个核心问题）\n- 研究目标（ SMART 格式）\n- 范围边界（ in-scope / out-of-scope）\n- 成功标准\n\n### Phase B: 文献发现与筛选\n\n搜索相关论文、博客、技术报告，筛选高质量来源。\n\n**输出：**\n- 关键词列表\n- 筛选出的文献列表（含标题、摘要、链接）\n- 文献质量评分\n\n### Phase C: 知识综合与假设生成\n\n整合文献发现，生成假设或研究问题。\n\n**输出：**\n- 知识图谱摘要\n- 核心发现列表\n- 假设 / 待验证命题\n\n### Phase D: 实验设计与执行\n\n设计验证假设的实验方案，包括数据、方法和评估指标。\n\n**输出：**\n- 实验设计方案\n- 数据需求\n- 评估指标\n\n### Phase E: 结果分析\n\n分析实验结果，生成洞察。\n\n**输出：**\n- 结果摘要\n- 统计显著性（如适用）\n- 洞察列表\n\n### Phase F: 论文撰写\n\n按学术论文结构输出完整内容。\n\n**输出：**\n- 标题 + 摘要\n- 引言\n- 相关工作\n- 方法\n- 结果\n- 讨论\n- 结论\n- 参考文献\n\n## 使用方式\n\n```\n用户: 研究 大语言模型在代码补全任务中的性能评估\n```\n\n或直接说：\n\n```\n用户: 自动研究 基于强化学习的机器人抓取策略\n```\n\n## 输出位置\n\n所有研究产物保存至：\n\n```\n$HOME/.openclaw/agents/main/agent/kb/raw/research-{课题名}-{日期}/\n```\n\n结构：\n```\nresearch-{课题}-{日期}/\n├── 00_scope.md        # Phase A 输出\n├── 01_discovery.md    # Phase B 输出\n├── 02_synthesis.md    # Phase C 输出\n├── 03_experiment.md   # Phase D 输出\n├── 04_analysis.md     # Phase E 输出\n├── 05_paper.md        # Phase F 输出（完整论文）\n└── log.txt            # 执行日志\n```\n\n## 人类在环（HITL）\n\n每个 Phase 完成后，脚本会：\n1. 显示该阶段产出摘要\n2. 询问用户：`继续下一步 / 调整参数 / 终止`\n3. 等待用户输入后执行下一阶段\n\n## 调用示例\n\n```bash\ncd ~/.openclaw/workspace/skills/huo15-research-pipeline\n./scripts/research.sh \"大语言模型在代码补全任务中的性能评估\"\n```\n\n## 依赖\n\n- `openclaw` CLI（用于 LLM 调用）\n- `curl`（用于 Web 搜索）\n- `jq`（用于 JSON 解析）\n- `obsidian-cli`（可选，用于直接写入 Obsidian）\n\n## 注意事项\n\n- 研究过程可能耗时较长，建议在空闲时运行\n- 每个 Phase 的产出都会保存，中断后可从断点继续\n- 论文撰写 Phase 会尽量保持学术规范，可直接提交或进一步编辑\n\nFile v1.0.1:_meta.json\n\n{\n  \"ownerId\": \"kn7byevkn40d6z4p7ghdb097z983tj33\",\n  \"slug\": \"huo15-research-pipeline\",\n  \"version\": \"1.0.1\",\n  \"publishedAt\": 1776791310196\n}\n\nArchive v1.0.0: 8 files, 10993 bytes\n\nFiles: scripts/research.sh (13021b), scripts/templates/phase_a_scope.sh (911b), scripts/templates/phase_b_discovery.sh (1100b), scripts/templates/phase_c_synthesis.sh (1226b), scripts/templates/phase_d_experiment.sh (1338b), scripts/templates/phase_g_write.sh (1835b), SKILL.md (4396b), _meta.json (142b)\n\nFile v1.0.0:SKILL.md\n\n# huo15-research-pipeline\n\n> 从想法到论文的全自主研究管道，灵感来自 AutoResearchClaw\n\n## 元信息\n\n- **version**: 1.0.0\n- **trigger**: 研究管道、research pipeline、自动研究、想法到论文、研究 [课题]\n- **author**: huo15\n- **compatibility**: OpenClaw >= 1.0\n\n## 功能概述\n\n将一个研究课题全自动推进至论文产出，涵盖范围定义、文献发现、知识综合、实验设计、结果分析与论文撰写。全程人类在环（HITL），每个 Phase 完成后等待用户确认。\n\n## 核心流程\n\n```\n用户: \"研究 [课题]\"\n         │\n         ▼\n  ┌─────────────────┐\n  │  Phase A: 范围定义  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase B: 文献发现  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase C: 知识综合  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase D: 实验设计  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase E: 结果分析  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase F: 论文撰写  │  → 完成\n  └────────┬────────┘\n           ▼\n      输出到 Obsidian\n```\n\n## Phase 详细说明\n\n### Phase A: 研究范围定义\n\n定义研究问题、目标、范围边界和成功标准。\n\n**输出：**\n- 研究问题（1-3 个核心问题）\n- 研究目标（ SMART 格式）\n- 范围边界（ in-scope / out-of-scope）\n- 成功标准\n\n### Phase B: 文献发现与筛选\n\n搜索相关论文、博客、技术报告，筛选高质量来源。\n\n**输出：**\n- 关键词列表\n- 筛选出的文献列表（含标题、摘要、链接）\n- 文献质量评分\n\n### Phase C: 知识综合与假设生成\n\n整合文献发现，生成假设或研究问题。\n\n**输出：**\n- 知识图谱摘要\n- 核心发现列表\n- 假设 / 待验证命题\n\n### Phase D: 实验设计与执行\n\n设计验证假设的实验方案，包括数据、方法和评估指标。\n\n**输出：**\n- 实验设计方案\n- 数据需求\n- 评估指标\n\n### Phase E: 结果分析\n\n分析实验结果，生成洞察。\n\n**输出：**\n- 结果摘要\n- 统计显著性（如适用）\n- 洞察列表\n\n### Phase F: 论文撰写\n\n按学术论文结构输出完整内容。\n\n**输出：**\n- 标题 + 摘要\n- 引言\n- 相关工作\n- 方法\n- 结果\n- 讨论\n- 结论\n- 参考文献\n\n## 使用方式\n\n```\n用户: 研究 大语言模型在代码补全任务中的性能评估\n```\n\n或直接说：\n\n```\n用户: 自动研究 基于强化学习的机器人抓取策略\n```\n\n## 输出位置\n\n所有研究产物保存至：\n\n```\n$HOME/.openclaw/agents/main/agent/kb/raw/research-{课题名}-{日期}/\n```\n\n结构：\n```\nresearch-{课题}-{日期}/\n├── 00_scope.md        # Phase A 输出\n├── 01_discovery.md    # Phase B 输出\n├── 02_synthesis.md    # Phase C 输出\n├── 03_experiment.md   # Phase D 输出\n├── 04_analysis.md     # Phase E 输出\n├── 05_paper.md        # Phase F 输出（完整论文）\n└── log.txt            # 执行日志\n```\n\n## 人类在环（HITL）\n\n每个 Phase 完成后，脚本会：\n1. 显示该阶段产出摘要\n2. 询问用户：`继续下一步 / 调整参数 / 终止`\n3. 等待用户输入后执行下一阶段\n\n## 调用示例\n\n```bash\ncd ~/.openclaw/workspace/skills/huo15-research-pipeline\n./scripts/research.sh \"大语言模型在代码补全任务中的性能评估\"\n```\n\n## 依赖\n\n- `openclaw` CLI（用于 LLM 调用）\n- `curl`（用于 Web 搜索）\n- `jq`（用于 JSON 解析）\n- `obsidian-cli`（可选，用于直接写入 Obsidian）\n\n## 注意事项\n\n- 研究过程可能耗时较长，建议在空闲时运行\n- 每个 Phase 的产出都会保存，中断后可从断点继续\n- 论文撰写 Phase 会尽量保持学术规范，可直接提交或进一步编辑\n\nFile v1.0.0:_meta.json\n\n{\n  \"ownerId\": \"kn7byevkn40d6z4p7ghdb097z983tj33\",\n  \"slug\": \"huo15-research-pipeline\",\n  \"version\": \"1.0.0\",\n  \"publishedAt\": 1776790893714\n}","readmeExcerpt":"Skill: Huo15 Research Pipeline Owner: zhaobod1 Summary: 从想法到论文的全自主研究管道，6阶段，含HITL，输出到Obsidian Tags: latest:1.0.3 Version history: v1.0.3 | 2026-04-24T04:15:33.588Z | auto - Version bump from 1.0.2 to 1.0.3. - No changes to files or functionality in this release. - Documentation and skill description remain unchanged. v1.0.2 | 2026-04-23T03:21:49.150Z | user v1.0.2 把本地工作态同步到 clawhub（之前本地版本号落后于 clawhub） v1.0.1 | 2026-04","codeSnippets":[],"executableExamples":[{"language":"text","snippet":"用户: \"研究 [课题]\"\n         │\n         ▼\n  ┌─────────────────┐\n  │  Phase A: 范围定义  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase B: 文献发现  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase C: 知识综合  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase D: 实验设计  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase E: 结果分析  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase F: 论文撰写  │  → 完成\n  └────────┬────────┘\n           ▼\n      输出到 Obsidian"},{"language":"text","snippet":"用户: 研究 大语言模型在代码补全任务中的性能评估"},{"language":"text","snippet":"用户: 自动研究 基于强化学习的机器人抓取策略"},{"language":"text","snippet":"$HOME/.openclaw/agents/main/agent/kb/raw/research-{课题名}-{日期}/"},{"language":"text","snippet":"research-{课题}-{日期}/\n├── 00_scope.md        # Phase A 输出\n├── 01_discovery.md    # Phase B 输出\n├── 02_synthesis.md    # Phase C 输出\n├── 03_experiment.md   # Phase D 输出\n├── 04_analysis.md     # Phase E 输出\n├── 05_paper.md        # Phase F 输出（完整论文）\n└── log.txt            # 执行日志"},{"language":"bash","snippet":"cd ~/.openclaw/workspace/skills/huo15-research-pipeline\n./scripts/research.sh \"大语言模型在代码补全任务中的性能评估\""}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: huo15-research-pipeline\nversion: 1.0.2\naliases:\n  - 火一五研究管道\n  - 火一五论文管道\n  - 自动研究\ndescription: 从想法到论文的全自主研究管道，6阶段，含HITL，输出到Obsidian\n---\n# huo15-research-pipeline\n\n> 从想法到论文的全自主研究管道，灵感来自 AutoResearchClaw\n\n## 元信息\n\n- **version**: 1.0.0\n- **trigger**: 研究管道、research pipeline、自动研究、想法到论文、研究 [课题]\n- **author**: huo15\n- **compatibility**: OpenClaw >= 1.0\n\n## 功能概述\n\n将一个研究课题全自动推进至论文产出，涵盖范围定义、文献发现、知识综合、实验设计、结果分析与论文撰写。全程人类在环（HITL），每个 Phase 完成后等待用户确认。\n\n## 核心流程\n\n```\n用户: \"研究 [课题]\"\n         │\n         ▼\n  ┌─────────────────┐\n  │  Phase A: 范围定义  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase B: 文献发现  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase C: 知识综合  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase D: 实验设计  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase E: 结果分析  │  → 用户确认\n  └────────┬────────┘\n           ▼\n  ┌─────────────────┐\n  │  Phase F: 论文撰写  │  → 完成\n  └────────┬────────┘\n           ▼\n      输出到 Obsidian\n```\n\n## Phase 详细说明\n\n### Phase A: 研究范围定义\n\n定义研究问题、目标、范围边界和成功标准。\n\n**输出：**\n- 研究问题（1-3 个核心问题）\n- 研究目标（ SMART 格式）\n- 范围边界（ in-scope / out-of-scope）\n- 成功标准\n\n### Phase B: 文献发现与筛选\n\n搜索相关论文、博客、技术报告，筛选高质量来源。\n\n**输出：**\n- 关键词列表\n- 筛选出的文献列表（含标题、摘要、链接）\n- 文献质量评分\n\n### Phase C: 知识综合与假设生成\n\n整合文献发现，生成假设或研究问题。\n\n**输出：**\n- 知识图谱摘要\n- 核心发现列表\n- 假设 / 待验证命题\n\n### Phase D: 实验设计与执行\n\n设计验证假设的实验方案，包括数据、方法和评估指标。\n\n**输出：**\n- 实验设计方案\n- 数据需求\n- 评估指标\n\n### Phase E: 结果分析\n\n分析实验结果，生成洞察。\n\n**输出：**\n- 结果摘要\n- 统计显著性（如适用）\n- 洞察列表\n\n### Phase F: 论文撰写\n\n按学术论文结构输出完整内容。\n\n**输出：**\n- 标题 + 摘要\n- 引言\n- 相关工作\n- 方法\n- 结果\n- 讨论\n- 结论\n- 参考文献\n\n## 使用方式\n\n```\n用户: 研究 大语言模型在代码补全任务中的性能评估\n```\n\n或直接说：\n\n```\n用户: 自动研究 基于强化学习的机器人抓取策略\n```\n\n## 输出位置\n\n所有研究产物保存至：\n\n```\n$HOME/.openclaw/agents/main/agent/kb/raw/research-{课题名}-{日期}/\n```\n\n结构：\n```\nresearch-{课题}-{日期}/\n├── 00_scope.md        # Phase A 输出\n├── 01_discovery.md    # Phase B 输出\n├── 02_synthesis.md    # Phase C 输出\n├── 03_experiment.md   # Phase D 输出\n├── 04_analysis.md     # Phase E 输出\n├── 05_paper.md        # Phase F 输出（完整论文）\n└── log.txt            # 执行日志\n```\n\n## 人类在环（HITL）\n\n每个 Phase 完成后，脚本会：\n1. 显示该阶段产出摘要\n2. 询问用户：`继续下一步 / 调整参数 / 终止`\n3. 等待用户输入后执行下一阶段\n\n## 调用示例\n\n```bash\ncd ~/.openclaw/workspace/skills/huo15-research-pipeline\n./scripts/research.sh \"大语言模型在代码补全任务中的性能评估\"\n```\n\n## 依赖\n\n- `openclaw` CLI（用于 LLM 调用）\n- `curl`（用于 Web 搜索）\n- `jq`（用于 JSON 解析）\n- `obsidian-cli`（可选，用于直接写入 Obsidian）\n\n## 注意事项\n\n- 研究过程可能耗时较长，建议在空闲时运行\n- 每个 Phase 的产出都会保存，中断后可从断点继续\n- 论文撰写 Phase 会尽量保持学术规范，可直接提交或进一步编辑"},{"path":"_meta.json","content":"{\n  \"ownerId\": \"kn7byevkn40d6z4p7ghdb097z983tj33\",\n  \"slug\": \"huo15-research-pipeline\",\n  \"version\": \"1.0.3\",\n  \"publishedAt\": 1777004133588\n}"},{"path":"skill-card.md","content":"## Description:\n\nA Chinese-language research pipeline that moves a topic through scope definition, literature discovery, synthesis, experiment design, analysis, and paper drafting with human confirmation between phases.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[zhaobod1](https://clawhub.ai/user/zhaobod1)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers, researchers, and OpenClaw users use this skill to turn an initial research topic into staged Markdown research artifacts and a draft academic paper. It is intended for workflows where a human reviews each phase before the next phase proceeds.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Research topics, prompts, and generated notes may be sent to the configured OpenClaw LLM provider.\n\nMitigation: Use only environments approved for the research data, and avoid confidential or proprietary topics unless that provider and environment are authorized.\n\nRisk: Generated research outputs are persisted under the OpenClaw knowledge-base path.\n\nMitigation: Review output locations, access controls, and retention before running the pipeline on sensitive topics.\n\nRisk: Obsidian integration is optional and may not automatically sync results in every environment.\n\nMitigation: Treat Obsidian export as a manual follow-up unless the local Obsidian command is installed and tested.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/zhaobod1/skills/huo15-research-pipeline)\n- [Publisher profile](https://clawhub.ai/user/zhaobod1)\n\n## Skill Output:\n\n**Output Type(s):** [text, markdown, shell commands, guidance]\n\n**Output Format:** [Markdown files and terminal prompts]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Creates staged research notes, a paper draft, and a log under the configured OpenClaw knowledge-base path.]\n\n## Skill Version(s):\n\n1.0.3 (source: server release metadata)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment."}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":"从想法到论文的全自主研究管道，6阶段，含HITL，输出到Obsidian Skill: Huo15 Research Pipeline Owner: zhaobod1 Summary: 从想法到论文的全自主研究管道，6阶段，含HITL，输出到Obsidian Tags: latest:1.0.3 Version history: v1.0.3 | 2026-04-24T04:15:33.588Z | auto - Version bump from 1.0.2 to 1.0.3. - No changes to files or functionality in this release. - Documentation and skill description remain unchanged. v1.0.2 | 2026-04-23T03:21:49.150Z | user v1.0.2 把本地工作态同步到 clawhub（之前本地版本号落后于 clawhub） v1.0.1 | 2026-04","editorialQuality":{"score":100,"threshold":65,"status":"ready","wordCount":830,"uniquenessScore":57,"reasons":[]}},"media":{"evidence":{"source":"no-media","verified":false,"confidence":"low","updatedAt":"2026-10-11T06:03:08.916Z","emptyReason":"No screenshots, media assets, or demo links are available."},"primaryImageUrl":null,"mediaAssetCount":0,"assets":[],"demoUrl":null},"ownerResources":{"evidence":{"source":"unclaimed","verified":false,"confidence":"low","updatedAt":"2026-10-11T06:03:08.916Z","emptyReason":"This page has not been claimed by the agent owner."},"hasCustomPage":false,"customPageUpdatedAt":null,"customLinks":[],"structuredLinks":{"docsUrl":null,"demoUrl":null,"supportUrl":null,"pricingUrl":null,"statusUrl":null},"customPage":null},"relatedAgents":{"evidence":{"source":"protocol-neighbors","verified":false,"confidence":"medium","updatedAt":"2026-10-11T08:45:05.447Z","emptyReason":null},"items":[{"id":"8ebccd8e-3863-4187-8355-c3f14e1f9edf","entityType":"agent","canonicalPath":"/agent/iofficeai-aionui","slug":"iofficeai-aionui","name":"AionUi","description":"Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!","url":"https://github.com/iOfficeAI/AionUi","homepage":"https://www.aionui.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-10-09T19:11:12.944Z","createdAt":"2026-02-25T03:38:16.584Z","downloads":null},{"id":"b917f68a-ebff-438e-84f8-3f4b2494c0bc","entityType":"agent","canonicalPath":"/agent/activepieces-activepieces","slug":"activepieces-activepieces","name":"activepieces","description":"AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents","url":"https://github.com/activepieces/activepieces","homepage":"https://www.activepieces.com","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-15T02:22:12.426Z","createdAt":"2026-02-25T03:38:12.412Z","downloads":null},{"id":"5cb26759-3a39-483f-94cf-276a98c13bb8","entityType":"agent","canonicalPath":"/agent/cherryhq-cherry-studio","slug":"cherryhq-cherry-studio","name":"cherry-studio","description":"AI productivity studio with smart chat, autonomous agents, and 300+ assistants. 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