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bdjobs-job-apply（bdjobs 工作申请）

Agent Skill

bdjobs-job-apply 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。

总安装

4,445

周安装

189

GitHub Stars

公开资料未说明

下载量

1,557
OpenClaw

安装说明

本站只整理中文说明和来源信息，不托管安装包，也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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：bdjobs-job-apply（bdjobs 工作申请）
来源仓库：https://github.com/sazidulalam47/bdjobs-job-apply
安装命令：
openclaw skills install bdjobs-job-apply
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 bdjobs-job-apply

简介

自动化 BDJobs 平台职位搜索、申请与薪资更新管理。

  • 适合求职者在孟加拉国市场批量投递简历或跟踪申请状态。
  • 通过 clawhub 安装后在 OpenClaw 中设置账号偏好后启动自动化流程。
  • 需用户提供合法登录凭据，并同意平台服务协议。
  • 建议定期检查申请记录，避免错过面试通知。bdjobs-job-apply 属于研究检索类 Skill，可作为该场景下的辅助能力补充。

SKILL.md

name
bdjobs-job-apply
description
BDJobs job search, matching, applying, undoing, and salary-update automation for OpenClaw. Use when the user wants to set up BDJobs credentials/preferences, search fresh non-applied jobs, inspect job details, auto-apply to matched jobs, cancel an application, or update expected salary.

BDJobs Job Apply

Use this skill to help a user manage BDJobs job searching and applying without needing to know APIs or code.

What this skill does

  • Save resume text/LaTeX into data/resume.md
  • Save credentials and preferences into data/userDetails.json
  • Log in and save auth data into data/loggedInData.json
  • Refresh applied jobs into data/appliedJobIds.json
  • Keep a not-liked list in data/notLikedJobIds.json
  • Search jobs and return raw job details for AI matching
  • Auto-apply to matched jobs when asked
  • Undo/cancel an applied job when asked
  • Update expected salary for an already applied job

Onboarding flow

When the user first sets up this skill, ask for these values in plain language:

  1. BDJobs username
  2. BDJobs password
  3. Resume text or LaTeX
  4. everyDayApplyCount (default: 2)
  5. everyDayCronTime (default: 12:00 PM)
  6. isFresher (yes/no)
  7. Experience in years
  8. Preferred jobLocation (optional, leave blank for all)

Save them in:

  • data/userDetails.json
  • data/resume.md

If the user has extra search filters or matching rules, store them in data/preferences.json.

Login flow

Before search/apply work, always ensure data/loggedInData.json exists.

If missing:

  1. run ChecKUsername
  2. take guidId
  3. run Login
  4. save token, refreshToken, encryptId, decodeId, and guidId to data/loggedInData.json

If login returns 401 at any point:

  1. run ChecKUsername again
  2. run Login again
  3. overwrite data/loggedInData.json

Search flow

When the user asks for fresh jobs:

  1. Clear data/suggestedJobs.json
  2. Run scripts/bdjobs-refresh-applied.js to update data/appliedJobIds.json from GetApplyPositionInfoV1
  3. Run scripts/bdjobs-fetch-jobs.js with --keyword, --isFresher, --postedWithin, --pg, and --jobLocation to fetch raw job lists from GetJobSearch
  4. Run scripts/bdjobs-filter-jobs.js to exclude already-applied and not-liked job IDs before Job-Details
  5. For selected job IDs, run scripts/bdjobs-job-details.js to fetch full job details
  6. Let AI compare the raw job details with data/resume.md and data/preferences.json
  7. Run scripts/bdjobs-rank-jobs.js to save the top 5 matched jobs into data/suggestedJobs.json
  8. Show the contents of data/suggestedJobs.json to the user

Recommended match threshold:

  • show apply suggestions only if match is above 40%
  • if the user asks for a looser list, show 30%+

AI matching details:

  • Compare the raw job details with data/resume.md and data/preferences.json
  • Judge fit from skills, education, age, experience, responsibilities, location, and preferences
  • Output a suggested job list with match percentages

Auto-apply flow

When the user asks to auto-apply:

  1. Ensure login exists
  2. Refresh applied jobs first
  3. Search fresh jobs
  4. Let AI score the raw job details against the resume and preferences
  5. For each approved job:

- call JobApply - read MinimumSalary - use it as expectedSalary in JobApplyPost - call JobApplyPost - if successful, always show matchingScore - if successful, add the job ID to data/appliedJobIds.json - save result in data/lastApplyResult.json

  1. Send Telegram notification only after success

Undo/cancel flow

When the user asks to undo an application:

  1. Ensure login exists
  2. Call UndoJobApply with job ID and FormValue
  3. If successful, remove the job ID from data/appliedJobIds.json
  4. Save result in data/lastUndoResult.json

Expected salary update flow

When the user asks to update salary for an applied job:

  1. Ensure login exists
  2. Call UpdateExpectedSalary
  3. Save result in data/lastSalaryUpdateResult.json

Files used by this skill

Important files live inside this skill folder:

  • data/resume.md
  • data/userDetails.json
  • data/loggedInData.json
  • data/appliedJobIds.json
  • data/notLikedJobIds.json
  • data/preferences.json
  • data/suggestedJobs.json
  • data/lastApplyResult.json
  • data/lastUndoResult.json
  • data/lastSalaryUpdateResult.json

Script entry points

Run scripts from the skill folder, not the workspace root:

  • scripts/init-job-profile.js
  • scripts/bdjobs-login.js
  • scripts/bdjobs-refresh-applied.js
  • scripts/bdjobs-fetch-jobs.js

bdjobs-fetch-jobs.js accepts:

  • --keyword=...
  • --isFresher=true|false
  • --postedWithin=... (optional day count, any number)
  • --pg=...
  • --jobLocation=...
  • scripts/bdjobs-filter-jobs.js
  • scripts/bdjobs-job-details.js accepts --jobId=... or a positional job id
  • scripts/bdjobs-rank-jobs.js
  • scripts/bdjobs-apply.js
  • scripts/bdjobs-undo.js
  • scripts/bdjobs-update-salary.js

Matching rules

Use the resume and these signals:

  • Job title
  • Company name
  • Job description
  • Education requirements
  • Age requirement
  • Experience requirement
  • Additional job requirements
  • Suggested skills
  • Job location
  • Job nature
  • User preferences from data/preferences.json

Helpful behavior

When presenting jobs to the user:

  • keep language simple
  • explain only what matters
  • include the direct job link
  • mention whether it looks worth applying

When the user wants automation, do the work directly with the scripts.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明，方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用；具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

84.98%
按下载量换算1,323

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API；具体网络访问范围需要结合源码和 README 复核。

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 warning/failed 结果，不能写成本站确认安全。当前只有一个来源，正式发布前建议补源仓库或其他目录站核验。

来源信息

GitHub 仓库

github.com

/sazidulalam47/bdjobs-job-apply

SKILL.md 来源

clawhub.ai

/sazidulalam47/bdjobs-job-apply

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