This skill should be used when the user wants to "optimize resume for job", "check ATS score", "improve resume bullets", "analyze resume gaps", "tailor resume to job description", "get ATS compatibility score", "improve bullet points", "match resume to job posting", "fix resume for ATS", or wants to maximize their resume's impact and ATS compatibility using the Placed platform at placed.exidian.tech.
AI-powered resume optimization for ATS compatibility, keyword matching, and bullet point quality — all via the Placed API. No MCP server required.
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>
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'])"
}
| Tool | Description |
|---|---|
check_ats_compatibility | ATS compatibility score and recommendations |
get_resume_quality_score | Overall quality score with section breakdown |
analyze_resume_gaps | Missing keywords and skills vs. a job description |
match_job | Score resume-job fit (0-100) with keyword breakdown |
optimize_resume_for_job | Tailor resume content to a specific job |
optimize_resume_section | Optimize a specific section (experience, skills, summary) |
improve_bullet_point | Rewrite a single bullet point with stronger impact |
generate_resume_from_prompt | Generate a complete resume from natural language |
Check ATS compatibility:
placed_call "check_ats_compatibility" '{"resume_id":"res_abc123"}'
# Returns: ATS score, formatting recommendations
Get quality score:
placed_call "get_resume_quality_score" '{"resume_id":"res_abc123"}'
# Returns: overall score, breakdown by section
Analyze gaps vs. a job description:
placed_call "analyze_resume_gaps" '{
"resume_id": "res_abc123",
"job_description": "Senior Software Engineer at Stripe — Go, distributed systems, Kafka..."
}'
# Returns: critical gaps, keyword gaps, suggestions
Score resume-job match:
placed_call "match_job" '{
"resume_id": "res_abc123",
"job_description": "..."
}'
# Returns: match score 0-100, matched/missing keywords
Optimize resume for a job:
placed_call "optimize_resume_for_job" '{
"resume_id": "res_abc123",
"job_description": "Senior Software Engineer at Airbnb..."
}'
# Returns: suggested section improvements
Improve a single bullet:
placed_call "improve_bullet_point" '{
"bullet_point": "Worked on database optimization",
"context": "Senior SRE at Uber"
}'
# Returns: rewritten bullet with metrics and impact
Optimize a specific section:
placed_call "optimize_resume_section" '{
"resume_id": "res_abc123",
"section_type": "experience",
"section_data": "Current bullets here...",
"job_description": "Target job description..."
}'
Run this before every application:
match_job — check current fit scoreanalyze_resume_gaps — identify missing keywordscheck_ats_compatibility — catch formatting issuesimprove_bullet_point — strengthen weak bulletsoptimize_resume_for_job — get full tailoring suggestionsmatch_job again — confirm score improved[Action Verb] + [What You Did] + [How/Scale] + [Quantified Result]
Before: "Worked on database optimization" After: "Optimized PostgreSQL query performance by 40%, reducing p99 latency from 500ms to 300ms for 10M+ daily users"
Strong action verbs:
| Issue | Fix |
|---|---|
| Tables or columns | Use single-column layout |
| Graphics or images | Remove all non-text elements |
| Unusual fonts | Use Arial, Calibri, or Times New Roman |
| Headers/footers with key info | Move to main body |
| Inconsistent date formats | Use MM/YYYY throughout |
| Missing job description keywords | Add naturally to skills and bullets |
match_job before and after optimizing to measure improvementoptimize_resume_for_job suggestions before applyingreferences/api-guide.md — Full API reference with scoring rubrics and response schemas