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placed-interview-coach安排面试教练

Agent Skill

placed-interview-coach 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

9,090

周安装

375

GitHub Stars

公开资料未说明

下载量

2,970
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:placed-interview-coach(安排面试教练)
来源仓库:https://github.com/ajitsingh25/placed-interview-coach
安装命令:
openclaw skills install placed-interview-coach
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install placed-interview-coach

简介

当用户想要“练习面试”、“模拟面试”、“准备面试”、“系统设计面试”、“行为界面”时,应该使用此技能。

SKILL.md

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"
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

ToolDescription
start_interview_sessionBegin a mock interview for a specific role
continue_interview_sessionSubmit your answer and get the next question
get_interview_feedbackGet full performance analysis for a session
list_interview_casesBrowse system design cases
start_system_designStart a system design interview
get_behavioral_questionsGet STAR-format behavioral questions
save_story_to_bankSave a STAR story for reuse
get_interview_questionsGenerate 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 question

Answer 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 question

Get 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

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

73.92%
按下载量换算2,195

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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