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Knowledge metabolism: Day 0 init (discuss + baseline survey) or daily cycle (incremental search + update knowledge + generate hypotheses). Triggered by bootstrap and daily cron.
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
Use this when the user needs to choose between multiple ML routes after survey but before committing to implementation. Compares candidate approaches, selects one, records rejected routes, and keeps a fallback.
Use this when the project needs real baseline results before or alongside the main model. Runs classical or literature-aligned baselines under the same protocol and writes a reproducible baseline summary.
Use this when the project needs a dedicated data-quality review before model review. Checks data reality, split correctness, label health, leakage risk, shape consistency, and mock-data disclosure.
Use this when the user wants a draft paper, figure bundle, README, release page, or experiment artifact reviewed before sharing. Checks evidence binding, claim scope, captions, layout clarity, and release readiness.
Use this when the user wants to improve chart quality, standardize plotting style, regenerate release figures, or add captions/protocol notes. Normalizes fonts, colors, legends, units, and scope notes across Scientify figures.
Use this when the user wants to improve README, docs pages, or microsites so a new reader can understand what the project is, how to use it, what artifacts exist, and what the scope boundaries are within one screen.
| name | metabolism |
| description | Knowledge metabolism: Day 0 init (discuss + baseline survey) or daily cycle (incremental search + update knowledge + generate hypotheses). Triggered by bootstrap and daily cron. |
读取 config.json 的 currentDay 字段判断执行哪个分支：
currentDay == 0 或 config.json 不存在 → 执行 Day 0（初始化）currentDay >= 1 → 执行每日增量循环与用户讨论研究方向后，构建领域基线知识。
config.json 是否存在
config.json（包含 keywords, arxivCategories, sources, currentDay: 0, processed_ids: []）currentDay > 0：跳转到每日循环委托 /research-collect 执行宽泛调研（不限日期），构建初始知识：
sessions_spawn({
task: "/research-collect\n研究主题: {从 config.json 的 keywords 提取}\n这是 Day 0 基线构建，请做宽泛调研（不限日期），覆盖领域经典工作和近期进展。",
label: "Day 0 Baseline Survey",
runTimeoutSeconds: 1800
})
等待完成后，读取 papers/ 获取论文列表。
对每篇论文：
将每篇论文的 arXiv ID / DOI 追加到 config.json 的 processed_ids。
创建 knowledge/_index.md：
为每个识别出的主题创建 knowledge/topic-{name}.md：
写入 log/{YYYY-MM-DD}-init.md，更新 config.json：currentDay 设为 1。
config.json 获取关键词、arXiv 分类、sources、processed_ids 和 currentDayknowledge/_index.md 获取当前知识状态根据 config.json 的 sources 字段选择搜索来源，用滑动窗口（过去 5 天）搜索，靠 processed_ids 去重：
arXiv（如果 sources 包含 "arxiv"）：
arxiv_search({
query: "{keywords} AND cat:{category}",
date_from: "{5天前 YYYY-MM-DD}",
sort_by: "submittedDate",
max_results: 30
})
OpenAlex（如果 sources 包含 "openalex"）：
openalex_search({
query: "{keywords}",
filter: "from_publication_date:{5天前 YYYY-MM-DD}",
sort: "publication_date",
max_results: 20
})
合并结果，按 arXiv ID / DOI 去重，跳过 processed_ids 中已有的论文。
按 /paper-download 的方式下载新论文到 papers/（arXiv 优先 .tex 源文件，DOI 通过 Unpaywall 获取 OA PDF）。
对每篇新论文：
将每篇论文的 arXiv ID / DOI 追加到 config.json 的 processed_ids。
读取当前 knowledge/_index.md 和相关 topic-*.md，根据今日阅读的论文更新。
更新原则：
篇幅管理： 每个 topic 文件控制在 200 行以内。接近上限时，压缩早期内容（合并相似结论、删除低价值条目），保留信息密度。不要为了压缩而丢失关键结论和来源引用。
更新完知识后，回顾今日新增内容，自问：
有想法 → 写入 ideas/hyp-{NNN}.md：
# Hypothesis {NNN}
## 假设
{一句话}
## 推理过程
{基于哪些论文/知识得出，2-3 段}
## 来源论文
- {arxiv_id}: {title}
## 自评
- 新颖性: {1-5}
- 可行性: {1-5}
- 影响力: {1-5}
然后用 sessions_send 通知 main session。
没有想法 → 跳过，不要硬凑。
写入 log/{YYYY-MM-DD}.md，更新 config.json：currentDay +1。