菜单
网页抓取与开放检索。Jina Reader（免费零配置）+ Firecrawl + Tavily + Exa + SerpAPI。题目背景涉及行业 / 政策 / 经济时启用；纯数学 / 物理机理题不启用。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Step 5 of the PaperOrchestra pipeline (arXiv:2604.05018). Iteratively refine drafts/paper.tex by simulating peer review and applying targeted revisions, with strict accept/revert halt rules. Maintains a worklog and snapshots each iteration so revert is real, not symbolic. TRIGGER when the orchestrator delegates Step 5 or when the user asks to "refine the draft", "iterate on the paper", or "run peer review on this paper".
Step 3 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the literature search strategy from outline.json — discover candidate papers via web search, verify them through Semantic Scholar (Levenshtein > 70 fuzzy title match, temporal cutoff, dedup by paperId), build a BibTeX file, and draft Introduction + Related Work using ≥90% of the verified pool. Runs in parallel with the plotting-agent. TRIGGER when the orchestrator delegates Step 3 or when the user asks to "find citations for my paper", "draft the related work", or "build the bibliography".
Step 1 of the PaperOrchestra pipeline (arXiv:2604.05018). Convert (idea.md, experimental_log.md, template.tex, conference_guidelines.md) into a strict JSON outline containing a plotting plan, literature search plan (Intro + Related Work), and section-level writing plan with citation hints. TRIGGER when the orchestrator delegates Step 1 or when the user asks to "outline a paper from raw materials" or "generate the paper structure".
Orchestrate the full PaperOrchestra (Song et al., 2026, arXiv:2604.05018) five-agent pipeline to turn unstructured research materials (idea, experimental log, LaTeX template, conference guidelines, optional figures) into a submission-ready LaTeX manuscript and compiled PDF. TRIGGER when the user asks to "write a paper from my experiments", "turn this idea and these results into a paper", "generate a conference submission", "run paper-orchestra on X", or otherwise wants the end-to-end paper-writing pipeline. Coordinates the outline-agent, plotting-agent, literature-review-agent, section-writing-agent, and content-refinement-agent skills.
Use when solving CUMCM, MCM, ICM, or other mathematical modeling tasks that need contest problem intake, model selection, Python solving, figures, paper writing, quality audit, and packaged deliverables.
Use when EZ_math_model needs to convert paper.md to paper.docx, read a DOCX problem statement, preserve equations and tables, or package a modeling report as a Word document.
| name | webcrawl |
| description | 网页抓取与开放检索。Jina Reader（免费零配置）+ Firecrawl + Tavily + Exa + SerpAPI。题目背景涉及行业 / 政策 / 经济时启用；纯数学 / 物理机理题不启用。 |
| read_when | ["题目背景涉及政策 / 行业 / 地理 / 经济","需要从网页拉取行业基准 / 标准","评价类题目需要业界对照"] |
有具体 URL 要读 → Jina Reader（免费，零配置）
失败 → Firecrawl scrape（要 EZMM_FIRECRAWL_KEY）
失败 → 让 LLM 用 WebFetch（最后兜底）
要先搜后读 → Tavily（要 EZMM_TAVILY_KEY）
/ Exa（要 EZMM_EXA_KEY）
/ SerpAPI（要 EZMM_SERPAPI_KEY）
全部不可用 → 让用户给具体 URL，再走单页抓取
# 任意 URL → markdown，零配置
$url = 'https://example.com/article'
Invoke-RestMethod -Uri "https://r.jina.ai/$url" -OutFile workdir/.../web/$(($url | Get-FileHash -Algorithm MD5).Hash.Substring(0,8)).md
import requests, os
r = requests.post(
"https://api.firecrawl.dev/v1/scrape",
headers={"Authorization": f"Bearer {os.environ['EZMM_FIRECRAWL_KEY']}"},
json={"url": "https://...", "formats": ["markdown"]},
timeout=60,
).json()
markdown = r["data"]["markdown"]
参考 tools/webcrawl/SKILL.md 的代码段。
抓回的页面落到：
workdir/{task_id}/attachments/external/web/<sha8>.md
文件头三行写：
<!-- source: tavily | firecrawl | jina | exa | serp -->
<!-- fetched_at: 2026-05-20T10:00:00+08:00 -->
<!-- url: https://... -->
robots.txt（除非用户授权）| 情况 | 处理 |
|---|---|
| 全部 key 缺失 | 仅 Jina 可用；写诊断说明可用工具集 |
| 单页 4xx / 5xx | 退避重试 1 次；仍失败记诊断 |
| 抓回登录墙 / 验证码 | 不绕过；写诊断 |
| 超时 > 60s | 中断，写诊断 |