Placed Career Tools

该 Skill 封装 Placed 外部接口，提供简历与职位匹配打分、简历差距分析、简历优化建议、求职信与领英资料生成、面试问题、公司薪资数据、薪资谈判脚本、录用分析及公司调研。使用需 Placed API 密钥（本地配置文件或环境变量），调用通过 curl 发送请求并用 python3 解析返回结果，内容由远端服务生成。

ajitsingh25

热度 55.89

最近更新 2026-05-11 17:31:45

分类：创作依赖：代码执行 / 读写文件 / 第三方 API应用场景：文案创作 / 研究 / 市场分析

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add placed-career-tools

Metadata

name: placed-career-tools
description: This skill should be used when the user wants to "match resume to job", "generate cover letter", "optimize resume for job", "get interview questions for company", "generate LinkedIn profile", "check application status", "get salary insights", "negotiate salary", "research company", "analyze resume gaps", or wants to use AI career tools from the Placed platform at placed.exidian.tech.
version: 1.0.0
metadata: {"openclaw":{"emoji":"🧭","homepage":"https://placed.exidian.tech"}}
tags: career,cover-letter,linkedin,salary,salary-negotiation,company-research,job-match,career-tools,placed,exidian,job-search,ai-career-coach

Placed Career Tools

Comprehensive AI career toolkit: job-resume matching, cover letters, LinkedIn optimization, salary insights, negotiation scripts, and company research — all via the Placed API. No MCP server required.

API Key

Load the key from ~/.config/placed/credentials, falling back to the environment:

if [ -z "$PLACED_API_KEY" ] && [ -f "$HOME/.config/placed/credentials" ]; then
  source "$HOME/.config/placed/credentials"
fi

If PLACED_API_KEY is still not set, ask the user:

"Please provide your Placed API key (get it at https://placed.exidian.tech/settings/api)"

Then save it for future sessions:

mkdir -p "$HOME/.config/placed"
echo "export PLACED_API_KEY=<key_provided_by_user>" > "$HOME/.config/placed/credentials"
export PLACED_API_KEY=<key_provided_by_user>

How to Call the API

placed_call() {
  local tool=$1
  local args=${2:-'{}'}
  curl -s -X POST https://placed.exidian.tech/api/mcp \
    -H "Authorization: Bearer $PLACED_API_KEY" \
    -H "Content-Type: application/json" \
    -d "{\"jsonrpc\":\"2.0\",\"id\":1,\"method\":\"tools/call\",\"params\":{\"name\":\"$tool\",\"arguments\":$args}}" \
    | python3 -c "import sys,json; d=json.load(sys.stdin); print(d['result']['content'][0]['text'])"
}

Available Tools

Resume-Job Matching

Tool	Description
`match_job`	Score how well a resume matches a job description
`analyze_resume_gaps`	Find missing keywords and skills for a target role
`optimize_resume_for_job`	Tailor resume content to a specific job

AI Writing Tools

Tool	Description
`generate_cover_letter`	Generate a tailored cover letter
`generate_linkedin_profile`	AI-optimized LinkedIn headline and About section
`get_interview_questions`	Get likely interview questions for a company/role

Salary & Negotiation

Tool	Description
`get_company_salary_data`	Market salary data by role and company
`generate_salary_negotiation_script`	Personalized salary negotiation script
`analyze_offer`	Analyze a job offer against market rates

Company Research

Tool	Description
`research_company`	Company overview, culture, news, interview tips

Usage Examples

Match resume to job:

placed_call "match_job" '{
  "resume_id": "res_abc123",
  "job_description": "Senior Software Engineer at Stripe — distributed systems, Go, Kubernetes..."
}'
# Returns: match score, matched keywords, missing keywords, recommendations

Analyze resume gaps:

placed_call "analyze_resume_gaps" '{
  "resume_id": "res_abc123",
  "job_description": "..."
}'

Generate cover letter:

placed_call "generate_cover_letter" '{
  "resume_id": "res_abc123",
  "company_name": "Airbnb",
  "job_title": "Staff Engineer",
  "job_description": "...",
  "tone": "professional"
}'

Get salary data:

placed_call "get_company_salary_data" '{
  "company_name": "Google",
  "position": "Senior Software Engineer",
  "location": "San Francisco, CA"
}'

Generate negotiation script:

placed_call "generate_salary_negotiation_script" '{
  "current_offer": 200000,
  "target_salary": 240000,
  "justification": [
    "6 years distributed systems experience",
    "Led 3 high-impact projects",
    "Market rate for this role in SF is $230-260K"
  ]
}'

Generate LinkedIn profile:

placed_call "generate_linkedin_profile" '{"resume_id":"res_abc123"}'

Research a company:

placed_call "research_company" '{"company_name":"Databricks"}'

Common Workflows

Before applying:

match_job — check resume-job fit score
analyze_resume_gaps — find missing keywords
optimize_resume_for_job (via placed-resume-optimizer) — tailor resume
generate_cover_letter — write tailored cover letter

Negotiate an offer:

get_company_salary_data — benchmark the offer
analyze_offer — get full market comparison
generate_salary_negotiation_script — get negotiation talking points

Additional Resources

references/api-guide.md — Full API reference with all parameters and response schemas