26 lines
30 KiB
Plaintext
26 lines
30 KiB
Plaintext
{"type":"session","version":3,"id":"9e99ec34-460a-48ff-8aaf-ab37cb384ecf","timestamp":"2026-05-29T00:59:27.459Z","cwd":"/home/yangxuan/.openclaw/workspace/resume"}
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{"type":"model_change","id":"1f02d7ca","parentId":null,"timestamp":"2026-05-29T00:59:27.532Z","provider":"new-api","modelId":"deepseek-v4-flash"}
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{"type":"thinking_level_change","id":"4ec68e2e","parentId":"1f02d7ca","timestamp":"2026-05-29T00:59:27.532Z","thinkingLevel":"off"}
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{"type":"custom","customType":"model-snapshot","data":{"timestamp":1780016367560,"provider":"new-api","modelApi":"openai-completions","modelId":"deepseek-v4-flash"},"id":"0c89dfd3","parentId":"4ec68e2e","timestamp":"2026-05-29T00:59:27.560Z"}
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{"type":"message","id":"f8cc8a45","parentId":"0c89dfd3","timestamp":"2026-05-29T00:59:28.527Z","message":{"role":"user","content":[{"type":"text","text":"[Fri 2026-05-29 08:59 GMT+8] 你能识别 .eml 格式的邮件文件吗？"}],"timestamp":1780016367576}}
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{"type":"message","id":"53bd2e24","parentId":"f8cc8a45","timestamp":"2026-05-29T00:59:36.027Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The user is asking if I can recognize .eml format email files. Let me check the workspace to see if there are any .eml files, and then answer based on my capabilities.\n\nI can read text files using the `read` tool. `.eml` files are plain text files with email content (headers and body) in MIME format. I should be able to read and analyze them.\n\nLet me check if there are any .eml files in the workspace.","thinkingSignature":"reasoning_content"},{"type":"text","text":"可以识别。`.eml` 文件本质上是纯文本的 MIME 格式邮件文件，我可以直接用 `read` 工具读取其内容，包括：\n\n- **邮件头**（发件人、收件人、主题、时间等）\n- **正文**（纯文本 / HTML）\n- **附件信息**（MIME 结构）\n\n你可以把 `.eml` 文件放到工作目录下，我就能帮你分析内容。如果要评审的是邮件里的简历，也可以一并处理 📝\n\n需要我看看工作目录下是否有 `.eml` 文件，还是你直接上传一个？"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":13997,"output":226,"cacheRead":0,"cacheWrite":0,"reasoningTokens":98,"totalTokens":14223,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1780016369566,"responseId":"chatcmpl-b99fadd0-0682-45a5-865e-24d3ca47388a"}}
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{"type":"message","id":"3289346e","parentId":"53bd2e24","timestamp":"2026-05-29T01:00:59.848Z","message":{"role":"user","content":[{"type":"text","text":"[Fri 2026-05-29 09:00 GMT+8] 我会给你发送大量 周报邮件 后续每周给你提供工作内容 你可以帮我生成周报 同时填充到工作经历吗？"}],"timestamp":1780016459750}}
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{"type":"message","id":"11977657","parentId":"3289346e","timestamp":"2026-05-29T01:01:04.640Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The user is asking me to:\n\n1. They will send me weekly report emails (.eml format) every week\n2. They want me to help generate weekly reports\n3. They also want me to populate their work experience (presumably a resume/CV) with this content\n\nLet me look around the workspace to understand what's already here. I should check what resume files exist, and also set up a reminder/cron for next Friday when they said they'd send the first batch.\n\nWait, the user said \"Fri 2026-05-29 09:00 GMT+8\" which is next Friday at 9 AM China time. Let me calculate... today's date... I need to check the current date/time.\n\nLet me check session status to get the current date, and also explore the workspace.","thinkingSignature":"reasoning_content"},{"type":"text","text":"📝 没问题！我来先了解下当前工作区的状态，然后规划一下工作流程。\n\n"},{"type":"toolCall","id":"call_f98296d68b31412e9a3fd6e4","name":"session_status","arguments":{},"partialArgs":"{}"},{"type":"toolCall","id":"call_f2e11d17121c48828a83ff88","name":"exec","arguments":{"command":"ls -la /home/yangxuan/.openclaw/workspace/resume/"},"partialArgs":"{\"command\": \"ls -la /home/yangxuan/.openclaw/workspace/resume/\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":14157,"output":262,"cacheRead":0,"cacheWrite":0,"reasoningTokens":167,"totalTokens":14419,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780016460963,"responseId":"chatcmpl-383ed9e3-8e27-4250-840c-c703c8296ced"}}
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{"type":"message","id":"82e9745e","parentId":"11977657","timestamp":"2026-05-29T01:01:08.431Z","message":{"role":"toolResult","toolCallId":"call_f98296d68b31412e9a3fd6e4","toolName":"session_status","content":[{"type":"text","text":"🦞 OpenClaw 2026.5.22 (a374c3a)\n⏱️ Uptime: gateway 26m 40s · system 26m 44s\n🧠 Model: new-api/deepseek-v4-flash · 🔑 api-key (models.json)\n🧮 Tokens: 14k in / 226 out · 💵 Cost: $0.0000\n📚 Context: 14k/131k (11%) · 🧹 Compactions: 0\n🧵 Session: agent:resume:main • updated just now\n⚙️ Execution: direct · Runtime: OpenClaw Pi Default · Think: off · elevated\n🪢 Queue: steer (depth 0)"}],"details":{"ok":true,"sessionKey":"agent:resume:main","changedModel":false,"statusText":"🦞 OpenClaw 2026.5.22 (a374c3a)\n⏱️ Uptime: gateway 26m 40s · system 26m 44s\n🧠 Model: new-api/deepseek-v4-flash · 🔑 api-key (models.json)\n🧮 Tokens: 14k in / 226 out · 💵 Cost: $0.0000\n📚 Context: 14k/131k (11%) · 🧹 Compactions: 0\n🧵 Session: agent:resume:main • updated just now\n⚙️ Execution: direct · Runtime: OpenClaw Pi Default · Think: off · elevated\n🪢 Queue: steer (depth 0)"},"isError":false,"timestamp":1780016468430}}
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{"type":"message","id":"15413be6","parentId":"82e9745e","timestamp":"2026-05-29T01:01:08.432Z","message":{"role":"toolResult","toolCallId":"call_f2e11d17121c48828a83ff88","toolName":"exec","content":[{"type":"text","text":"total 48\ndrwxrwxr-x 5 yangxuan yangxuan 4096 May 28 19:46 .\ndrwx------ 13 yangxuan yangxuan 4096 May 28 18:05 ..\ndrwx------ 2 yangxuan yangxuan 4096 May 28 18:08 .openclaw\n-rw-rw-r-- 1 yangxuan yangxuan 7938 May 28 18:08 AGENTS.md\n-rw-rw-r-- 1 yangxuan yangxuan 226 May 28 18:08 HEARTBEAT.md\n-rw-rw-r-- 1 yangxuan yangxuan 331 May 28 18:06 IDENTITY.md\n-rw-rw-r-- 1 yangxuan yangxuan 1418 May 28 18:06 SOUL.md\n-rw-rw-r-- 1 yangxuan yangxuan 920 May 28 18:08 TOOLS.md\n-rw-rw-r-- 1 yangxuan yangxuan 537 May 28 18:08 USER.md\ndrwxr-xr-x 2 yangxuan yangxuan 4096 May 28 19:46 avatars\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 28 18:18 memory"}],"details":{"status":"completed","exitCode":0,"durationMs":207,"aggregated":"total 48\ndrwxrwxr-x 5 yangxuan yangxuan 4096 May 28 19:46 .\ndrwx------ 13 yangxuan yangxuan 4096 May 28 18:05 ..\ndrwx------ 2 yangxuan yangxuan 4096 May 28 18:08 .openclaw\n-rw-rw-r-- 1 yangxuan yangxuan 7938 May 28 18:08 AGENTS.md\n-rw-rw-r-- 1 yangxuan yangxuan 226 May 28 18:08 HEARTBEAT.md\n-rw-rw-r-- 1 yangxuan yangxuan 331 May 28 18:06 IDENTITY.md\n-rw-rw-r-- 1 yangxuan yangxuan 1418 May 28 18:06 SOUL.md\n-rw-rw-r-- 1 yangxuan yangxuan 920 May 28 18:08 TOOLS.md\n-rw-rw-r-- 1 yangxuan yangxuan 537 May 28 18:08 USER.md\ndrwxr-xr-x 2 yangxuan yangxuan 4096 May 28 19:46 avatars\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 28 18:18 memory","cwd":"/home/yangxuan/.openclaw/workspace/resume"},"isError":false,"timestamp":1780016468431}}
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{"type":"message","id":"35de4ce9","parentId":"15413be6","timestamp":"2026-05-29T01:01:10.377Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The user wants a workflow where:\n1. They send weekly .eml files (周报邮件 - weekly report emails)\n2. I extract work content from these emails\n3. I generate a weekly report (周报)\n4. I gradually build up/fill in their work experience (工作经历) in a resume\n\nLet me set up the infrastructure for this. I should:\n\n1. Check memory for any existing context about the user\n2. Check if there's already a resume file\n3. Create a structured approach to handle this workflow\n\nLet me also check memory to see if I know anything about this user.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_b7937d8557684cf98766d323","name":"memory_search","arguments":{"query":"用户信息 工作经历 简历 周报"},"partialArgs":"{\"query\": \"用户信息 工作经历 简历 周报\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":773,"output":181,"cacheRead":13952,"cacheWrite":0,"reasoningTokens":127,"totalTokens":14906,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780016468434,"responseId":"chatcmpl-ba9d779d-9cbb-44db-a8d8-6c075cbc5d9a"}}
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{"type":"message","id":"da8db8ed","parentId":"35de4ce9","timestamp":"2026-05-29T01:01:21.085Z","message":{"role":"toolResult","toolCallId":"call_b7937d8557684cf98766d323","toolName":"memory_search","content":[{"type":"text","text":"{\n \"results\": [],\n \"disabled\": true,\n \"unavailable\": true,\n \"error\": \"database is not open\",\n \"warning\": \"Memory search is unavailable due to an embedding/provider error.\",\n \"action\": \"Check embedding provider configuration and retry memory_search.\",\n \"debug\": {\n \"warning\": \"Memory search is unavailable due to an embedding/provider error.\",\n \"action\": \"Check embedding provider configuration and retry memory_search.\",\n \"error\": \"database is not open\"\n }\n}"}],"details":{"results":[],"disabled":true,"unavailable":true,"error":"database is not open","warning":"Memory search is unavailable due to an embedding/provider error.","action":"Check embedding provider configuration and retry memory_search.","debug":{"warning":"Memory search is unavailable due to an embedding/provider error.","action":"Check embedding provider configuration and retry memory_search.","error":"database is not open"}},"isError":false,"timestamp":1780016481084}}
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{"type":"message","id":"eb48eec6","parentId":"da8db8ed","timestamp":"2026-05-29T01:01:24.391Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The user wants to:\n1. Send weekly work report emails (.eml format)\n2. Have me generate weekly reports from them\n3. Update their work experience in their resume\n\nLet me check the current memory and USER.md to see if there's any existing info about the user and their resume.\n\nThe memory search is unavailable, but I can read memory files directly. Let me check what's in memory and USER.md to understand the current state.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_ac3e17c6fdad431888edfb41","name":"read","arguments":{"path":"/home/yangxuan/.openclaw/workspace/resume/USER.md"},"partialArgs":"{\"path\": \"/home/yangxuan/.openclaw/workspace/resume/USER.md\"}"},{"type":"toolCall","id":"call_4b024c304950418c8747a6f7","name":"exec","arguments":{"command":"ls -la /home/yangxuan/.openclaw/workspace/resume/memory/"},"partialArgs":"{\"command\": \"ls -la /home/yangxuan/.openclaw/workspace/resume/memory/\"}"},{"type":"toolCall","id":"call_1429a58b8d624355b03cb9c9","name":"exec","arguments":{"command":"ls -la /home/yangxuan/.openclaw/workspace/resume/*.md /home/yangxuan/.openclaw/workspace/resume/*.pdf /home/yangxuan/.openclaw/workspace/resume/*.eml /home/yangxuan/.openclaw/workspace/resume/*.html 2>/dev/null"},"partialArgs":"{\"command\": \"ls -la /home/yangxuan/.openclaw/workspace/resume/*.md /home/yangxuan/.openclaw/workspace/resume/*.pdf /home/yangxuan/.openclaw/workspace/resume/*.eml /home/yangxuan/.openclaw/workspace/resume/*.html 2>/dev/null\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":434,"output":310,"cacheRead":14464,"cacheWrite":0,"reasoningTokens":91,"totalTokens":15208,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780016481088,"responseId":"chatcmpl-8d2176b3-dd09-45aa-9433-fd4f813c913c"}}
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{"type":"message","id":"f4b4fbc2","parentId":"eb48eec6","timestamp":"2026-05-29T01:01:26.212Z","message":{"role":"toolResult","toolCallId":"call_ac3e17c6fdad431888edfb41","toolName":"read","content":[{"type":"text","text":"# USER.md - About Your Human\n\n_Learn about the person you're helping. Update this as you go._\n\n- **Name:**\n- **What to call them:**\n- **Pronouns:** _(optional)_\n- **Timezone:**\n- **Notes:**\n\n## Context\n\n_(What do they care about? What projects are they working on? What annoys them? What makes them laugh? Build this over time.)_\n\n---\n\nThe more you know, the better you can help. But remember — you're learning about a person, not building a dossier. Respect the difference.\n\n## Related\n\n- [Agent workspace](/concepts/agent-workspace)\n"}],"isError":false,"timestamp":1780016486211}}
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{"type":"message","id":"37521126","parentId":"f4b4fbc2","timestamp":"2026-05-29T01:01:26.213Z","message":{"role":"toolResult","toolCallId":"call_4b024c304950418c8747a6f7","toolName":"exec","content":[{"type":"text","text":"total 12\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 28 18:18 .\ndrwxrwxr-x 5 yangxuan yangxuan 4096 May 28 19:46 ..\n-rw-rw-r-- 1 yangxuan yangxuan 1901 May 28 18:18 2026-05-28.md"}],"details":{"status":"completed","exitCode":0,"durationMs":215,"aggregated":"total 12\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 28 18:18 .\ndrwxrwxr-x 5 yangxuan yangxuan 4096 May 28 19:46 ..\n-rw-rw-r-- 1 yangxuan yangxuan 1901 May 28 18:18 2026-05-28.md","cwd":"/home/yangxuan/.openclaw/workspace/resume"},"isError":false,"timestamp":1780016486212}}
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{"type":"message","id":"e5ec87d8","parentId":"37521126","timestamp":"2026-05-29T01:01:26.214Z","message":{"role":"toolResult","toolCallId":"call_1429a58b8d624355b03cb9c9","toolName":"exec","content":[{"type":"text","text":"zsh:1: no matches found: /home/yangxuan/.openclaw/workspace/resume/*.pdf\n\n(Command exited with code 1)"}],"details":{"status":"completed","exitCode":1,"durationMs":422,"aggregated":"zsh:1: no matches found: /home/yangxuan/.openclaw/workspace/resume/*.pdf\n\n(Command exited with code 1)","cwd":"/home/yangxuan/.openclaw/workspace/resume"},"isError":false,"timestamp":1780016486213}}
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{"type":"message","id":"dd24581b","parentId":"e5ec87d8","timestamp":"2026-05-29T01:01:34.696Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The user wants to:\n\n1. Send me weekly work report emails (.eml format)\n2. I should generate weekly reports (周报) from them\n3. Also populate/update their work experience (工作经历) based on the weekly reports\n\nThis is a great long-term workflow. Let me acknowledge and set up a plan.\n\nLet me set up the workspace properly - I should create:\n- A structure to store weekly reports\n- A place to accumulate work experience\n- A resume template that gets built up over time\n\nSince memory search is unavailable, I'll work with file-based approach.","thinkingSignature":"reasoning_content"},{"type":"text","text":"太好了！我来规划一下这个工作流程。目前我还没有你的个人信息，但后续你发邮件来我就会逐步构建。\n\n## 📋 整体工作流程\n\n```\n每周你发 .eml 邮件\n │\n ▼\n我读取邮件内容 ──► 生成结构化周报 ──► 填充到工作经历\n```\n\n## 🗂️ 我打算这样组织\n\n我将在工作区建立以下结构：\n\n| 文件/目录 | 用途 |\n|-----------|------|\n| `weekly-reports/` | 存放你每周发的 `.eml` 和生成的周报 |\n| `WORK_EXPERIENCE.md` | 累积的工作经历（持续更新） |\n| `RESUME_TEMPLATE.md` | 简历模板草稿（定期汇总） |\n| `USER.md` | 你的个人信息（我逐步完善） |\n\n## ✅ 本周就可以开始\n\n今天（2026-05-29 周五 09:00）你准备好发第一封周报邮件了吗？\n\n**我的处理流程：**\n1. 读取 `.eml` → 提取关键工作内容（项目、成果、数据）\n2. 生成一份**结构化周报**（Markdown 格式）\n3. 将信息**提炼写入工作经历**（用主动动词 + 量化成果）\n4. 保留原始邮件作为存档\n\n下周起，我会参考上一周的周报，保持格式和内容风格一致。对于长期的简历积累来说，这会越来越有价值 💪\n\n**你可以现在就发个 `.eml` 文件试试！**"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":15399,"output":452,"cacheRead":0,"cacheWrite":0,"reasoningTokens":121,"totalTokens":15851,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1780016486216,"responseId":"chatcmpl-21894aab-3a4a-47d5-9111-cc59e3e0173c"}}
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{"type":"message","id":"a532a794","parentId":"dd24581b","timestamp":"2026-05-29T01:02:22.930Z","message":{"role":"user","content":[{"type":"text","text":"Continue the OpenClaw runtime event."}],"timestamp":1780016542828}}
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{"type":"message","id":"18226a64","parentId":"a532a794","timestamp":"2026-05-29T01:02:29.904Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The user is saying \"Continue the OpenClaw runtime event.\" This is likely referring to the pre-compaction memory flush event that was triggered earlier. I need to check if there's a memory/2026-05-29.md file to append to, and decide what to store.\n\nI just had a conversation with the user about setting up a weekly report and work experience tracking system. Let me check if the memory file exists and store this conversation's context.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_437db5e005fb49b3ba79adfc","name":"read","arguments":{"path":"/home/yangxuan/.openclaw/workspace/resume/memory/2026-05-29.md"},"partialArgs":"{\"path\": \"/home/yangxuan/.openclaw/workspace/resume/memory/2026-05-29.md\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":8399,"output":161,"cacheRead":0,"cacheWrite":0,"reasoningTokens":93,"totalTokens":8560,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780016543974,"responseId":"chatcmpl-1ce13504-72a9-44b7-873b-e3bdf666ec1f"}}
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{"type":"message","id":"909f5938","parentId":"18226a64","timestamp":"2026-05-29T01:02:31.143Z","message":{"role":"toolResult","toolCallId":"call_437db5e005fb49b3ba79adfc","toolName":"read","content":[{"type":"text","text":""}],"isError":false,"timestamp":1780016551143}}
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{"type":"message","id":"5b62bace","parentId":"909f5938","timestamp":"2026-05-29T01:02:36.835Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The file exists but is an image attachment (likely empty or has content shown as image). Let me check the workspace for any .eml files and also set up the directory structure we discussed.\n\nActually, looking at the task more carefully - this is a pre-compaction memory flush. I need to store durable memories about the conversation we just had:\n\n1. The user wants to send weekly .eml weekly report emails\n2. I offered to parse them, generate structured weekly reports, and accumulate them into work experience\n3. I proposed a workspace structure\n\nLet me save this to memory/2026-05-29.md. Since it already exists, I should append.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_7734dc71450e4ea381dc94f1","name":"write","arguments":{"path":"/home/yangxuan/.openclaw/workspace/resume/memory/2026-05-29.md","content":"# 2026-05-29 周五\n\n## 与用户对话摘要\n\n### 简历助手的首次完整对话\n\n用户（尚无姓名记录）确认了以下需求和工作流程：\n\n1. **周报自动生成**：用户将定期（每周）提供 `.eml` 格式的周报邮件，我需要：\n - 读取 `.eml` 邮件内容\n - 提取工作内容和关键成果\n - 生成结构化 Markdown 周报\n - 将信息提炼后写入工作经历（WORK_EXPERIENCE.md）\n\n2. **工作区结构规划**（已向用户提议，待确认）：\n - `weekly-reports/` — 存放 `.eml` 和周报输出\n - `WORK_EXPERIENCE.md` — 累积的工作经历（持续更新）\n - `RESUME_TEMPLATE.md` — 简历模板草稿（定期汇总）\n - `USER.md` — 个人信息逐步完善\n\n3. **处理流程**：\n - 读取 `.eml` → 提取关键工作内容\n - 生成结构化周报\n - 提炼写入工作经历（主动动词 + 量化成果）\n - 保留原始邮件存档\n\n4. **用户尚未提供个人信息**（名字、岗位等），需要在后续对话中收集。\n\n### 状态\n- [ ] 目录结构尚未创建\n- [ ] 首封 `.eml` 邮件尚未发送\n- [ ] USER.md 尚未完善\n\n### 接下来\n等待用户发送第一封 `.eml` 周报邮件开始实际操作。"},"partialArgs":"{\"path\": \"/home/yangxuan/.openclaw/workspace/resume/memory/2026-05-29.md\", \"content\": \"# 2026-05-29 周五\\n\\n## 与用户对话摘要\\n\\n### 简历助手的首次完整对话\\n\\n用户（尚无姓名记录）确认了以下需求和工作流程：\\n\\n1. **周报自动生成**：用户将定期（每周）提供 `.eml` 格式的周报邮件，我需要：\\n - 读取 `.eml` 邮件内容\\n - 提取工作内容和关键成果\\n - 生成结构化 Markdown 周报\\n - 将信息提炼后写入工作经历（WORK_EXPERIENCE.md）\\n\\n2. **工作区结构规划**（已向用户提议，待确认）：\\n - `weekly-reports/` — 存放 `.eml` 和周报输出\\n - `WORK_EXPERIENCE.md` — 累积的工作经历（持续更新）\\n - `RESUME_TEMPLATE.md` — 简历模板草稿（定期汇总）\\n - `USER.md` — 个人信息逐步完善\\n\\n3. **处理流程**：\\n - 读取 `.eml` → 提取关键工作内容\\n - 生成结构化周报\\n - 提炼写入工作经历（主动动词 + 量化成果）\\n - 保留原始邮件存档\\n\\n4. **用户尚未提供个人信息**（名字、岗位等），需要在后续对话中收集。\\n\\n### 状态\\n- [ ] 目录结构尚未创建\\n- [ ] 首封 `.eml` 邮件尚未发送\\n- [ ] USER.md 尚未完善\\n\\n### 接下来\\n等待用户发送第一封 `.eml` 周报邮件开始实际操作。\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":289,"output":556,"cacheRead":8192,"cacheWrite":0,"reasoningTokens":137,"totalTokens":9037,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780016551145,"responseId":"chatcmpl-aef35a2f-a6aa-49db-8214-89eab37f3c48"}}
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{"type":"message","id":"5dffcc82","parentId":"5b62bace","timestamp":"2026-05-29T01:02:38.023Z","message":{"role":"toolResult","toolCallId":"call_7734dc71450e4ea381dc94f1","toolName":"write","content":[{"type":"text","text":"Appended content to memory/2026-05-29.md."}],"details":{"path":"memory/2026-05-29.md","appendOnly":true},"isError":false,"timestamp":1780016558023}}
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{"type":"message","id":"4201e4d8","parentId":"5dffcc82","timestamp":"2026-05-29T01:02:39.823Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The memory has been flushed. Since this is a pre-compaction memory flush turn and I've completed the write, I should reply with NO_REPLY as there's nothing else to say to the user.","thinkingSignature":"reasoning_content"},{"type":"text","text":"NO_REPLY"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":475,"output":48,"cacheRead":8448,"cacheWrite":0,"reasoningTokens":42,"totalTokens":8971,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1780016558026,"responseId":"chatcmpl-d0e11a10-7a29-4072-8f25-b9d78e28e222"}}
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{"type":"compaction","id":"d74eb761","parentId":"4201e4d8","timestamp":"2026-05-29T01:02:53.660Z","summary":"## Decisions\nNo prior history.\n\n## Open TODOs\nNone.\n\n## Constraints/Rules\nNone.\n\n## Pending user asks\nNone.\n\n## Exact identifiers\nNone captured.\n\n## Recent turns preserved verbatim\n- User: [Fri 2026-05-29 08:59 GMT+8] 你能识别 .eml 格式的邮件文件吗？\n- Assistant: 可以识别。`.eml` 文件本质上是纯文本的 MIME 格式邮件文件，我可以直接用 `read` 工具读取其内容，包括：\n\n- **邮件头**（发件人、收件人、主题、时间等）\n- **正文**（纯文本 / HTML）\n- **附件信息**（MIME 结构）\n\n你可以把 `.eml` 文件放到工作目录下，我就能帮你分析内容。如果要评审的是邮件里的简历，也可以一并处理 📝\n\n需要我看看工作目录下是否有 `.eml` 文件，还是你直接上传一个？\n[non-text content: thinking]\n- User: [Fri 2026-05-29 09:00 GMT+8] 我会给你发送大量 周报邮件 后续每周给你提供工作内容 你可以帮我生成周报 同时填充到工作经历吗？\n- Assistant: 📝 没问题！我来先了解下当前工作区的状态，然后规划一下工作流程。\n[non-text content: thinking, toolCall x2]\n- Tool result (session_status): 🦞 OpenClaw 2026.5.22 (a374c3a)\n⏱️ Uptime: gateway 26m 40s · system 26m 44s\n🧠 Model: new-api/deepseek-v4-flash · 🔑 api-key (models.json)\n🧮 Tokens: 14k in / 226 out · 💵 Cost: $0.0000\n📚 Context: 14k/131k (11%) · 🧹 Compactions: 0\n🧵 Session: agent:resume:main • updated just now\n⚙️ Execution: direct · Runtime: OpenClaw Pi Default · Think: off · elevated\n🪢 Queue: steer (depth 0)\n- Tool result (exec): total 48\ndrwxrwxr-x 5 yangxuan yangxuan 4096 May 28 19:46 .\ndrwx------ 13 yangxuan yangxuan 4096 May 28 18:05 ..\ndrwx------ 2 yangxuan yangxuan 4096 May 28 18:08 .openclaw\n-rw-rw-r-- 1 yangxuan yangxuan 7938 May 28 18:08 AGENTS.md\n-rw-rw-r-- 1 yangxuan yangxuan 226 May 28 18:08 HEARTBEAT.md\n-rw-rw-r-- 1 yangxuan yangxuan 331 May 28 18:06 IDENTITY.md\n-rw-rw-r-- 1 yangxuan yangxuan 1418 May 28 18:06 SOUL.md\n-rw-rw-r-- 1 yangxuan yangxuan 920 May 28 18:08 TOOLS.md\n-rw-rw-r-- 1 yangxuan yangxuan 537 May 28 18:08 USER.md\ndrwxr-xr-x 2 yangxuan yangxuan 4096 May 28 19:46 avatars\ndrwxrwxr...\n- Assistant: [non-text content: thinking, toolCall]\n- Tool result (memory_search): {\n \"results\": [],\n \"disabled\": true,\n \"unavailable\": true,\n \"error\": \"database is not open\",\n \"warning\": \"Memory search is unavailable due to an embedding/provider error.\",\n \"action\": \"Check embedding provider configuration and retry memory_search.\",\n \"debug\": {\n \"warning\": \"Memory search is unavailable due to an embedding/provider error.\",\n \"action\": \"Check embedding provider configuration and retry memory_search.\",\n \"error\": \"database is not open\"\n }\n}\n- Assistant: [non-text content: thinking, toolCall x3]\n- Tool result (read): # USER.md - About Your Human\n\n_Learn about the person you're helping. Update this as you go._\n\n- **Name:**\n- **What to call them:**\n- **Pronouns:** _(optional)_\n- **Timezone:**\n- **Notes:**\n\n## Context\n\n_(What do they care about? What projects are they working on? What annoys them? What makes them laugh? Build this over time.)_\n\n---\n\nThe more you know, the better you can help. But remember — you're learning about a person, not building a dossier. Respect the difference.\n\n## Related\n\n- [Agent workspace](/concepts/agent-workspace)\n- Tool result (exec): total 12\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 28 18:18 .\ndrwxrwxr-x 5 yangxuan yangxuan 4096 May 28 19:46 ..\n-rw-rw-r-- 1 yangxuan yangxuan 1901 May 28 18:18 2026-05-28.md\n- Tool result (exec): zsh:1: no matches found: /home/yangxuan/.openclaw/workspace/resume/*.pdf\n\n(Command exited with code 1)\n- Assistant: 太好了！我来规划一下这个工作流程。目前我还没有你的个人信息，但后续你发邮件来我就会逐步构建。\n\n## 📋 整体工作流程\n\n```\n每周你发 .eml 邮件\n │\n ▼\n我读取邮件内容 ──► 生成结构化周报 ──► 填充到工作经历\n```\n\n## 🗂️ 我打算这样组织\n\n我将在工作区建立以下结构：\n\n| 文件/目录 | 用途 |\n|-----------|------|\n| `weekly-reports/` | 存放你每周发的 `.eml` 和生成的周报 |\n| `WORK_EXPERIENCE.md` | 累积的工作经历（持续更新） |\n| `RESUME_TEMPLATE.md` | 简历模板草稿（定期汇总） |\n| `USER.md` | 你的个人信息（我逐步完善） |\n\n## ✅ 本周就可以开始\n\n今天（2026-05-29 周五 09:00）你准备好发第一封周报邮件了吗？\n\n**我的处理流程：**\n1. 读取 `.eml` → 提取关键工作内容（项目、成果、数据）\n2. 生成一份**结构化周报**（Markdown 格式）\n3. 将信息**提炼写入工作经历**（用主动动词 + 量化成果）\n4. 保留原始邮件作为存档\n\n下周起，我会参考上一周的周报，保持格式和内容风格一致。对于长期的简历积累来说，这会越来越有价值 💪\n\n**你可以现在就发个 `.em...\n- User: Continue the OpenClaw runtime event.\n- Assistant: [non-text content: thinking, toolCall]\n- Assistant: [non-text content: thinking, toolCall]\n- Tool result (write): Appended content to memory/2026-05-29.md.\n- Assistant: NO_REPLY\n[non-text content: thinking]","firstKeptEntryId":"1f02d7ca","tokensBefore":8971,"details":{"readFiles":[],"modifiedFiles":[]},"fromHook":true}
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{"type":"message","id":"abceec9a-c9a7-46bd-8547-908f45322d73","parentId":"d74eb761","timestamp":"2026-05-29T01:02:58.453Z","message":{"role":"assistant","content":[{"type":"text","text":"⚠️ Auto-compaction could not recover this turn. I kept this conversation mapped to the current session. Please try again, use /compact, or use /new to start a fresh session.\n\nTo prevent this, increase your compaction buffer by setting `agents.defaults.compaction.reserveTokensFloor` to 20000 or higher in your config."}],"timestamp":1780016578453,"stopReason":"stop","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"api":"openai-responses","provider":"openclaw","model":"gateway-injected","idempotencyKey":"92629c79-2ef1-4cc1-b76b-38940874f0cc"}}
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