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Agent Skill · 研究检索

employee-skills-importer(员工技能进口商)

employee-skills-importer 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

employee-skills-importer 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为权限未标注;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,674 个 Skill 里排第 6,412。

总安装 22,252周安装 909GitHub Stars 公开资料未说明下载 7,127核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:employee-skills-importer(员工技能进口商)
来源仓库:https://github.com/inna-demidova/employee-skills-importer
安装命令:
openclaw skills install employee-skills-importer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install employee-skills-importer

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

员工技能导入器解析 CSV 文件并将个人技能映射至数据库中的员工 ID。适用于 HR 系统中技能库建设与人员能力图谱更新场景。输出幂等 SQL 语句以避免重复插入造成数据混乱。使用前需验证 CSV 字段结构与数据库表字段匹配度。建议在非高峰期运行批量导入任务以减少系统负载。

employee-skills-importer 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install employee-skills-importer;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    权限没有明确标注,第一次使用时只给一个无关紧要的任务,观察它到底读了哪些文件和网络。

常见问题

6 条

employee-skills-importer 怎么安装?

在终端执行 openclaw skills install employee-skills-importer。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

employee-skills-importer 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

employee-skills-importer 需要什么权限?

权限级别没有明确标注。第一次使用时建议只给无关紧要的任务,观察它实际读写了哪些内容。

employee-skills-importer 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

employee-skills-importer 用的人多吗?

公开数据是累计安装 22,252 次,近一周安装 909 次,下载 7,127 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

employee-skills-importer 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
employee-skills-importer

员工技能进口商 · 本页

22,252—权限未标注MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
employee-skills-importer
description
Parse employee skills CSV files, identify skill categories and individual skills, look up employee IDs from an employees table, and generate idempotent SQL INSERT statements for skill_categories, skills, and employee_skills tables.

Employee Skills Importer

This skill automates the process of importing employee skills from CSV files into a Supabase database. It parses the CSV, checks what already exists in the database, and generates idempotent SQL scripts to insert missing data.

Overview

The skill performs a 3-step process:

  1. Identify and insert missing skill categories - Extract categories from CSV headers, check database, generate INSERT script
  2. Identify and insert missing skills - Extract skills with their categories, check database, generate INSERT script
  3. Generate employee_skills INSERT script - Map employees by name, link skills, create final INSERT statements

CSV Format Requirements

The CSV must have:

  • Row 1: Empty or metadata (ignored)
  • Row 2: Skill category names spanning multiple columns
  • Row 3+: Individual skill names (column headers, may span multiple rows due to line breaks)
  • Employee data rows: Employee data with First Name, Last Name in first two columns, followed by skill experience values

Example structure:

,,,,,,.NET,,,,,Front-end,,,Java,,,
First Name,Last Name,Full Name,Unit,...,C#,ASP.net,MVC,...,JavaScript,HTML,CSS,...,Java,Spring,...
John,Doe,John Doe,Unit 1,...,5,4,3,...,6,6,5,...,0,0,...

Workflow

Step 1: Skill Categories

  1. Parse row 2 to extract unique category names
  2. Query the database to check existing categories:
   SELECT name FROM skill_categories
  1. Generate idempotent INSERT for missing categories:
   INSERT INTO skill_categories (name) 
   VALUES ('Category1'), ('Category2'), ('Category3')
   ON CONFLICT (name) DO NOTHING;

Step 2: Skills

  1. Parse skill name rows and map to categories from row 2
  2. Query database for existing skills:
   SELECT s.name, sc.name as category_name 
   FROM skills s 
   LEFT JOIN skill_categories sc ON s.category_id = sc.id
  1. For each skill to insert:

- Find the category_id using a subquery - Generate idempotent INSERT:

   INSERT INTO skills (name, category_id)
   VALUES 
     ('C#', (SELECT id FROM skill_categories WHERE name = '.NET')),
     ('JavaScript', (SELECT id FROM skill_categories WHERE name = 'Front-end'))
   ON CONFLICT (name) DO NOTHING;

Step 3: Employee Skills

  1. Parse employee rows (first_name, last_name, skill values)
  2. Query employees table to get employee IDs:
   SELECT id, first_name, last_name FROM employees
  1. For each employee, for each skill with non-zero experience:

- Look up employee_id by matching first_name + last_name - Look up skill_id using subquery - CRITICAL: Use TRIM() in WHERE clause to handle whitespace variations in database - Generate INSERT:

   INSERT INTO employee_skills (employee_id, skill_id, years_of_experience)
   VALUES 
     (
       (SELECT id FROM employees WHERE TRIM(first_name) = 'John' AND TRIM(last_name) = 'Doe'),
       (SELECT id FROM skills WHERE name = 'C#'),
       5
     )
   ON CONFLICT (employee_id, skill_id) DO UPDATE 
   SET years_of_experience = EXCLUDED.years_of_experience;

Important Notes

Database Schema

  • skill_categories table: id (uuid), name (text, unique)
  • skills table: id (uuid), name (text, unique), category_id (uuid FK to skill_categories)
  • employees table: id (uuid), first_name (text), last_name (text)
  • employee_skills table: id (uuid), employee_id (uuid FK), skill_id (uuid FK), years_of_experience (real)

Idempotency

All generated SQL scripts use ON CONFLICT clauses to ensure they can be run multiple times without errors:

  • For categories and skills: ON CONFLICT (name) DO NOTHING
  • For employee_skills: ON CONFLICT (employee_id, skill_id) DO UPDATE SET years_of_experience = EXCLUDED.years_of_experience

Data Handling

  • Skip employees with zero or empty experience values for a skill
  • Handle numeric experience values (can be integers or decimals like 0.5, 1.7, etc.)
  • Clean up skill names by trimming whitespace and removing line breaks
  • Skip rows where employee lookup fails (employee not found in database)
  • Handle multi-line CSV cells properly
  • CRITICAL: Deduplicate employee-skill pairs before generating SQL - Keep the highest years value when duplicates exist
  • CRITICAL: Automatically correct employee name spellings - Use fuzzy matching to find and correct minor spelling differences (e.g., "Victoriia" → "Viktoriia")
  • CRITICAL: Trim all employee names - Remove leading/trailing whitespace from all names
  • CRITICAL: Use TRIM() in SQL WHERE clauses - Database may have extra spaces (e.g., "Yurii Solokha" with 3 spaces)
  • CRITICAL: Skip employees with no match - If no close match found in database, exclude those records and report them

Error Prevention

  • Always use subqueries for foreign key lookups rather than hardcoding UUIDs
  • Validate that category names match between row 2 and skill lookups
  • Report any employees from CSV not found in the database
  • Report any skills that couldn't be mapped to categories

CRITICAL - Prevent Duplicate Key Violations:

  1. Before generating the employee_skills INSERT, deduplicate all records by (first_name, last_name, skill)
  2. When duplicates exist, keep the record with the highest years_of_experience value
  3. This prevents: ON CONFLICT DO UPDATE command cannot affect row a second time

CRITICAL - Automatic Name Correction:

  1. Before generating SQL, validate ALL employees exist in the database
  2. For employees not found by exact match:

- Use fuzzy matching (Levenshtein distance or similar) to find close matches in database - If a close match is found (e.g., "Victoriia" → "Viktoriia"), automatically use the database spelling - If no close match is found, skip the employee entirely

  1. Generate a report showing:

- Employees with automatic corrections applied: "CSV name → Database name" - Employees skipped (no match found): List with number of skills skipped

  1. This prevents: null value in column "employee_id" violates not-null constraint

Output Format

The skill produces three SQL scripts plus one report file:

1_insert_categories.sql

-- Insert missing skill categories
INSERT INTO skill_categories (name) 
VALUES ('.NET'), ('Front-end'), ('Java')
ON CONFLICT (name) DO NOTHING;

2_insert_skills.sql

-- Insert missing skills with category mapping
INSERT INTO skills (name, category_id)
VALUES 
  ('C#', (SELECT id FROM skill_categories WHERE name = '.NET')),
  ('ASP.net', (SELECT id FROM skill_categories WHERE name = '.NET')),
  ('JavaScript', (SELECT id FROM skill_categories WHERE name = 'Front-end'))
ON CONFLICT (name) DO NOTHING;

3_insert_employee_skills.sql

-- Insert employee skills
-- Records have been deduplicated and filtered for valid employees only
-- Using TRIM() in WHERE clause to handle whitespace in database
INSERT INTO employee_skills (employee_id, skill_id, years_of_experience)
VALUES 
  (
    (SELECT id FROM employees WHERE TRIM(first_name) = 'John' AND TRIM(last_name) = 'Doe'),
    (SELECT id FROM skills WHERE name = 'C#'),
    5
  ),
  (
    (SELECT id FROM employees WHERE TRIM(first_name) = 'John' AND TRIM(last_name) = 'Doe'),
    (SELECT id FROM skills WHERE name = 'JavaScript'),
    6
  )
ON CONFLICT (employee_id, skill_id) DO UPDATE 
SET years_of_experience = EXCLUDED.years_of_experience;

Execution Steps

When the user provides a CSV file:

  1. Parse the CSV structure

- Read the file and validate format - Extract category names from row 2 - Extract skill names from subsequent rows (handling multi-line cells) - Map each skill to its category based on column positions

  1. Query existing data from Supabase

- Fetch all existing skill_categories - Fetch all existing skills with their categories - Fetch all employees (id, first_name, last_name)

  1. Generate Script 1: Categories

- Compare CSV categories against database - Create INSERT statement for missing categories - Save to file and present to user

  1. Generate Script 2: Skills

- Compare CSV skills against database - For missing skills, include category lookup subquery - Create INSERT statement - Save to file and present to user

  1. Generate Script 3: Employee Skills

- Parse employee rows - VALIDATE: Compare all CSV employees against database using exact matching - FUZZY MATCH: For non-exact matches, find closest database employee using similarity algorithm - Calculate similarity score for first_name and last_name separately - If combined similarity is above threshold (e.g., 85%), automatically use database name - Track all automatic corrections for reporting - CORRECT: Replace CSV names with database names for matched employees - FILTER: Skip employees with no close match found - DEDUPLICATE: Remove duplicates by (employee, skill), keeping highest years value - Generate INSERT statements using corrected employee names - Generate report showing corrections and skipped employees - Save SQL file and report to outputs directory - Present both files to user

  1. Present all files to the user

- Three SQL scripts (1_insert_categories.sql, 2_insert_skills.sql, 3_insert_employee_skills.sql) - One report file (skipped_employees_report.txt) if any employees were skipped - User can execute SQL scripts in order: 1 → 2 → 3 - User should review report to fix name mismatches if needed

Usage Example

User uploads CSV file and says: "Parse this employee skills CSV and generate SQL insert scripts"

Skill responds:

  1. Analyzes the CSV structure
  2. Connects to Supabase SkillsSystem project
  3. Checks existing data in all three tables
  4. Generates three SQL files
  5. Reports summary (e.g., "Found 5 new categories, 23 new skills, generating inserts for 47 employees")
  6. Presents the three SQL files for download

Project Configuration

This skill is configured to work with the Supabase project:

  • Project Name: SkillsSystem
  • Project ID: ypibfhbklinkvybgotef
  • Region: eu-central-1

The skill automatically connects to this project when executing queries.

Common Errors and Solutions

Error 1: "ON CONFLICT DO UPDATE command cannot affect row a second time"

Cause: Duplicate employee-skill pairs in the generated INSERT statement Solution: The skill now deduplicates all records before generating SQL. If you see this error, it means deduplication was not performed. Prevention: Always deduplicate by (first_name, last_name, skill) and keep the highest years value

Error 2: "null value in column 'employee_id' violates not-null constraint"

Cause: Employee from CSV not found in database (usually due to name spelling differences or whitespace issues) Solution: The skill now:

  1. Automatically corrects spelling differences using fuzzy matching
  2. Trims all whitespace from names
  3. Uses TRIM() in SQL WHERE clauses to match database records with extra spaces

Common issues:

  • Spelling variations: "Victoriia"↔"Viktoriia", "Karasyov"↔"Karasov"
  • Extra whitespace in database: "Yurii Solokha" (3 spaces)
  • Leading/trailing spaces

How it works:

  • Compares CSV names against database using similarity algorithm
  • If close match found (>83% similarity), automatically uses database spelling
  • Trims all names before comparison
  • Uses TRIM(first_name) and TRIM(last_name) in SQL to handle database whitespace
  • If no close match found, skips the employee and reports it

Result: This error should no longer occur as names are automatically corrected and whitespace is handled

Name Matching Algorithm

The skill uses the following approach:

  1. Try exact match first (first_name AND last_name)
  2. If no exact match, calculate similarity score using:

- Levenshtein distance or similar algorithm - Handles common variations: "Victoriia"↔"Viktoriia", "Karasyov"↔"Karasov"

  1. If similarity > 83% threshold, accept as match
  2. If multiple close matches found, pick the closest one
  3. If no close match, skip the employee
  4. Always trim whitespace from both CSV and database names
  5. Use TRIM() in SQL queries to match records with extra spaces in database

平台分布

OpenClaw

72.2%
按下载量换算5,146

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

未展示

权限和风险

权限未标注

当前来源未能明确判断权限范围,默认进入异常复核队列。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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