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Job Hunter

作者 sharbel · GitHub ↗ · v1.0.0
cross-platform ⚠ suspicious
966
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2
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7
当前安装
1
版本数
在 OpenClaw 中安装
/install job-hunter
功能描述
Assist with finding, evaluating, and applying to jobs using multi-source searches, fit scoring, application support, interview prep, and status tracking.
使用说明 (SKILL.md)

Job Hunter

End-to-end job search assistant — from finding opportunities to landing interviews.

Quick Start

1. Set up candidate profile

Create a profile JSON for the user. Use the template at {baseDir}/references/profile-template.json as a starting point. Ask the user about:

  • Target roles and seniority level
  • Key skills and tools
  • Location preferences (cities + remote)
  • Salary expectations
  • Dealbreakers and excluded companies
  • Preferred industries/domains

Save as profile.json in the workspace.

2. Search for jobs

Use the web_search tool with multiple queries to cast a wide net:

site:linkedin.com/jobs "[role]" "[city]"
site:indeed.com "[role]" "[city]"  
site:glassdoor.com/job "[role]" "[city]"
"[role]" "[city]" hiring 2025 2026

Expand keywords — don't just search one title. See {baseDir}/references/search-strategies.md for keyword expansion patterns.

Alternative: run the search script if Brave API is available:

{baseDir}/scripts/search_jobs.sh "CX Manager" --location "Amsterdam" --days 7

3. Evaluate fit

For each job found, run fit analysis:

python3 {baseDir}/scripts/analyze_fit.py --profile profile.json --jobs jobs.json --threshold 50

Or evaluate manually using this framework:

  • Skill match (40%): Does user have 60%+ of required skills?
  • Seniority match (25%): Right level — not over/under qualified?
  • Location match (15%): Compatible location or remote?
  • Domain match (10%): Preferred industry/domain?
  • Red flags (10%): Excluded companies? Dealbreakers?

Score: 🟢 75+ great | 🟡 55-74 good | 🟠 40-54 stretch | 🔴 \x3C40 skip

4. Present results

For each job, present:

  • Role & Company with direct link
  • Fit score with color indicator
  • Why it's a match (top 3 skill matches)
  • Gaps to address (missing skills to highlight as "eager to learn")
  • Salary estimate if available
  • Recommendation: Apply / Maybe / Skip

Application Support

Cover letters

Read {baseDir}/references/cover-letter-guide.md for structure and tone guidelines. Generate tailored cover letters that:

  • Reference specific company details (not generic)
  • Map user's experience to top 2-3 job requirements
  • Include quantified achievements
  • Stay under 350 words

Interview prep

Read {baseDir}/references/interview-prep.md for complete preparation framework. Help with:

  • Company research summaries
  • STAR stories for key requirements
  • Tailored "tell me about yourself" script
  • Salary negotiation talking points
  • Questions to ask the interviewer

Salary research

bash {baseDir}/scripts/salary_research.sh "Job Title" "Location"

Cross-reference 3+ sources. In the Netherlands: factor in 8% holiday allowance, possible 13th month, pension.

Daily Brief Format

When running as a scheduled job search brief:

  1. New opportunities — jobs found in last 24h with fit scores and direct links
  2. Application status — updates on pending applications
  3. Action items — what to apply to today, follow-ups due
  4. Market intel — industry trends, salary movements, hiring patterns

Tracking

Maintain a job tracker with:

  • Company, role, date found, source URL
  • Fit score and recommendation
  • Status: newappliedscreeninginterviewoffer/rejected/ghosted
  • Applied/skipped with reason
  • Contact info and follow-up dates

Tips for Agents

  • Never apply on behalf of the user — present opportunities, let them decide
  • Don't overwhelm — 3-5 quality matches beat 20 mediocre ones
  • Track excluded companies — never suggest the same company twice after rejection
  • Be honest about fit — stretches are okay to flag, but don't oversell poor matches
  • Respect dealbreakers — if user said no customer service, don't suggest it even if "it's a great company"
  • Update the profile — as you learn user preferences, refine the profile
  • Celebrate wins — applied to a job? Got an interview? Acknowledge it
安全使用建议
This skill appears to implement a legitimate job-search assistant, but note these concerns before installing or running it: - The search script conditionally uses a BRAVE_API_KEY environment variable to call the Brave Search API, but the skill metadata does not declare this requirement. If you provide a Brave API key, the script will send queries and receive results from api.search.brave.com. - If you are security-conscious, do not place sensitive credentials (cloud credentials, company tokens, or personal API keys unrelated to Brave) in the same environment where this skill runs. Treat BRAVE_API_KEY like a secret: only provide it if you understand and trust the endpoint. - Consider running the included scripts manually in a sandboxed environment first (with a dummy BRAVE_API_KEY or without it) to inspect the network traffic and outputs. The skill will fall back to producing search queries for manual use if no BRAVE_API_KEY is present. - Ask the skill author to update the manifest to declare required env vars (BRAVE_API_KEY) and to document where network requests go and what data is transmitted. Also request explicit documentation about what the skill will send to external services and whether any logs or outputs could contain user profile data. - If you want to be extra cautious, disable autonomous invocation for this skill (or restrict when it can run) and only invoke it manually after reviewing inputs/outputs.
功能分析
Type: OpenClaw Skill Name: job-hunter Version: 1.0.0 The skill bundle is classified as suspicious due to critical shell injection vulnerabilities found in `scripts/salary_research.sh` and `scripts/search_jobs.sh`. These scripts directly embed user-controlled input (e.g., job title, location) into shell commands without robust sanitization, potentially allowing an attacker to execute arbitrary commands if they can control the input provided to the agent. Additionally, `scripts/search_jobs.sh` performs external network calls to `https://api.search.brave.com` using an API key, which, while aligned with the stated purpose, represents a significant capability that could be misused if the underlying vulnerabilities were exploited.
能力评估
Purpose & Capability
Name/description, SKILL.md, reference docs, and the three scripts are coherent: they focus on searching job boards, scoring fit, salary research, and generating application assets. The included scripts and templates are proportional to a job-hunter assistant. One capability (calling the Brave search API) is plausible for multi-source searching, but the skill metadata does not declare the associated credential.
Instruction Scope
SKILL.md instructs the agent to run local scripts and use web_search/web_fetch to query third-party job sites — expected for this purpose. However, the search script also reads BRAVE_API_KEY from the environment and will call https://api.search.brave.com when present; that environment dependency and outbound network calls are not declared in the skill metadata. The SKILL.md does not warn the user that an API key may be used or that network requests will be made to the Brave API.
Install Mechanism
Instruction-only skill with no install spec. No external archives or installers are fetched by the platform when installing the skill itself. The scripts require common tools (python3, curl) but those are expected and not installed by the skill.
Credentials
Declared requirements list no environment variables, but scripts reference an environment variable (BRAVE_API_KEY) to enable the Brave API search path. This is an undeclared credential requirement. Supplying such a token would expose it to the script and any tool that executes it; the skill does not request or document other credentials, which is inconsistent with the code.
Persistence & Privilege
The skill does not request permanent presence (always: false) and has no install-time hooks or config writes in the manifest. It performs network calls at runtime if executed, but it does not request elevated agent privileges or attempt to modify other skills/configs.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install job-hunter
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /job-hunter 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release: multi-source job search, fit scoring, interview prep, cover letter guide, salary research
元数据
Slug job-hunter
版本 1.0.0
许可证
累计安装 7
当前安装数 7
历史版本数 1
常见问题

Job Hunter 是什么?

Assist with finding, evaluating, and applying to jobs using multi-source searches, fit scoring, application support, interview prep, and status tracking. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 966 次。

如何安装 Job Hunter?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install job-hunter」即可一键安装,无需额外配置。

Job Hunter 是免费的吗?

是的,Job Hunter 完全免费(开源免费),可自由下载、安装和使用。

Job Hunter 支持哪些平台?

Job Hunter 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Job Hunter?

由 sharbel(@sharbelayy)开发并维护,当前版本 v1.0.0。

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