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

AI Writing Tools

Salary & Negotiation

Company Research

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:

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

Negotiate an offer:

1. get_company_salary_data — benchmark the offer
2. analyze_offer — get full market comparison
3. generate_salary_negotiation_script — get negotiation talking points

Additional Resources

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