中文
ProHR5 nodes
Score 76

AI Resume Screening

Batch-parse resumes into structured talent pools: OCR, field extraction, skill taxonomy mapping, scoring, and Excel output — one pipeline, zero manual entry.

What does this workflow do?

PDF 版面分析与全文提取 → AI 语义解析(多维度简历信息提取)→ 技能标准化映射(LinkedIn 技能分类体系)→ 工作经历时间线校验与空档期检测 → 岗位匹配度评分(基于 JD 关键词相似度 + 经验权重)→ 重复候选人检测与合并 → 结构化 Excel 输出(可筛选/排序)

System flow

PDF 版面分析与全文提取 → AI 语义解析(多维度简历信息提取)→ 技能标准化映射(LinkedIn 技能分类体系)→ 工作经历时间线校验与空档期检测 → 岗位匹配度评分(基于 JD 关键词相似度 + 经验权重)→ 重复候选人检测与合并 → 结构化 Excel 输出(可筛选/排序)

Pipeline breakdown

PyPDF pdf LLM Reasoning text Pandas json LLM Reasoning json OpenPyXL json
  1. PyPDF pypdf — PDF text and metadata extraction, page-level splitting pdf → text
  2. LLM Reasoning llm — Large-language-model step that extracts, classifies, validates or writes structured output text → json
  3. Pandas pandas — Tabular compute — join, aggregate, validate and reshape the extracted records json → json
  4. LLM Reasoning llm — Large-language-model step that extracts, classifies, validates or writes structured output json → json
  5. OpenPyXL openpyxl — Writes a formatted, formula-ready Excel workbook as the deliverable json → xlsx

Workflow Reputation Score

Based on executions, success rate, update frequency, component quality, and user rating.

76Overall
★★★★★ 4.4
▶Executions
30
✓Success rate
100
↻Update frequency
85
⚙Component quality
90
★User rating
88

Based on executions, success rate, update frequency, component quality, and user rating.

Components used

PyPDFpypdf

PDF text and metadata extraction, page-level splitting

py-pdf/pypdf ↗
LLM Reasoningllm

Large-language-model step that extracts, classifies, validates or writes structured output

FlowSync proprietary
Pandaspandas

Tabular compute — join, aggregate, validate and reshape the extracted records

pandas-dev/pandas ↗
OpenPyXLopenpyxl

Writes a formatted, formula-ready Excel workbook as the deliverable

theorchard/openpyxl ↗

How is this different from n8n or Zapier?

Unlike generic workflow builders, FlowSync workflows ship pre-configured with AI skills baked into every node — OCR, LLM reasoning, transcription, super-resolution — not just webhook triggers. Each node is white-box auditable: you see input, output, and config. Deployment is instant — no self-hosting, no API-key per node.

Use cases

  • 校招/社招批量初筛
  • 猎头候选人库建设
  • 多岗位并行招聘
  • 人才库数字化管理

Author & Source

This workflow is maintained by the FlowSync team. All components are open-source or commercially licensed. Source code for each component is linked in the Components section above.

Pricing: Free tier available · 30% commission on forks · PRO tier · Official

Field notes

校招 5000 份简历,HireEZ 年费 $3000+。FlowSync Pro $19/月搞定,匹配度评分比 HireEZ 还准。

— HR 总监 陈, 互联网 HRD

批量解析后按技能标签检索,候选人匹配效率提升 10 倍。

— 猎头 Mike, 高端猎头

Data handling

简历中个人敏感信息仅在本次编排中使用。原始 PDF 不保留。结构化数据仅存储于您的账户。支持 GDPR 标准的数据删除请求。

FlowSync Workflow Marketplace · 76 reputation score · 30% execution · 100% success · 5-node white-box pipeline · maintained by FlowSync Official

Ready to run?

Batch-parse resumes into structured talent pools: OCR, field extraction, skill taxonomy mapping, scoring, and Excel output — one pipeline, zero manual entry.