- name
- placed-interview-coach
- description
- This skill should be used when the user wants to "practice interview", "mock interview", "prepare for interview", "system design interview", "behavioral interview", "STAR stories", "interview coaching", "get interview questions", or wants to prepare for technical interviews using the Placed career platform at placed.exidian.tech.
- version
- 1.0.0
- metadata
- tags
- interview,interview-prep,mock-interview,behavioral-interview,system-design-interview,star-method,interview-questions,interview-coaching,technical-interview,placed,exidian,career
Placed Interview Coach
AI-powered interview preparation via the Placed API. No MCP server required — all calls are made directly with curl.
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 "$HOME/.config/placed/credentials"
fiIf PLACED_API_KEY is still not set, ask the user:
"Please provide your Placed API key (get it at https://placed.exidian.tech/settings/api)"
Then save it for future sessions:
mkdir -p "$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
| Tool | Description |
|---|---|
start_interview_session | Begin a mock interview for a specific role |
continue_interview_session | Submit your answer and get the next question |
get_interview_feedback | Get full performance analysis for a session |
list_interview_cases | Browse system design cases |
start_system_design | Start a system design interview |
get_behavioral_questions | Get STAR-format behavioral questions |
save_story_to_bank | Save a STAR story for reuse |
get_interview_questions | Generate likely questions for a role/company |
Usage Examples
Start a mock interview:
placed_call "start_interview_session" '{
"resume_id": "res_abc123",
"job_title": "Senior Software Engineer",
"difficulty": "hard",
"company": "Google"
}'
# Returns: session_id + first questionAnswer a question:
placed_call "continue_interview_session" '{
"session_id": "sess_abc123",
"user_answer": "I would approach this by first clarifying requirements..."
}'
# Returns: feedback on your answer + next questionGet session feedback:
placed_call "get_interview_feedback" '{"session_id":"sess_abc123"}'List system design cases:
placed_call "list_interview_cases"
# Returns: Design Twitter, Design URL Shortener, Design Netflix, Design Uber, etc.Start a system design interview:
placed_call "start_system_design" '{"case_id":"design-twitter","difficulty":"senior"}'Get behavioral questions:
placed_call "get_behavioral_questions" '{
"target_role": "Engineering Manager",
"focus_categories": ["leadership", "conflict-resolution", "failure"]
}'Save a STAR story:
placed_call "save_story_to_bank" '{
"situation": "Led team through major refactor",
"task": "Reduce technical debt while shipping features",
"action": "Created phased plan, mentored junior devs, set clear milestones",
"result": "30% faster deployments, reduced bugs by 25%",
"category": "leadership"
}'Interview Types
Technical (Coding)
- Difficulty:
easy,medium,hard - Clarify requirements → code → explain trade-offs → test with examples
System Design
Framework: Requirements → High-Level Architecture → Database Design → Scalability → Fault Tolerance → Trade-offs
Behavioral
Use the STAR method for every answer:
- Situation — Context and background
- Task — Your responsibility
- Action — What you specifically did
- Result — Outcome with metrics
Tips
- Think out loud during technical interviews — explain your reasoning
- Start system design with constraints and scale requirements
- Use specific metrics in STAR answers ("reduced latency by 40%")
- Save strong stories to the bank so they're reusable across interviews
- Practice the same case at different difficulty levels to build confidence