Placed Career Tools

这是基于Placed API的综合AI职业工具，核心功能涵盖简历-岗位匹配、求职信/LinkedIn资料生成、薪资调研与谈判脚本撰写、公司调研等。典型场景包括求职申请前优化简历与求职信、收到offer后开展薪资谈判。首次使用需提供Placed API密钥，工具会自动保存密钥，调用对应接口传入参数即可输出匹配分数、定制化文案等结果，无需MCP服务器。

ajitsingh25

热度 56.04

最近更新 2026-05-11 17:31:45

分类：自动化依赖：第三方 API / 读写文件应用场景：文案创作 / 研究 / 数据处理 / 财务

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