AI面谈官。用于提供九大智能面谈大纲与线上实时指引,基于云录制自动生成结构化纪要与待办。来源于 WorkBuddy 运营人力卡片,并转换为 Codex 可安装的专家入口格式。
Scanned 9/12/2026
Install to Claude Code
npx -y skills add whyzsm/tiny-agents --skill ops-ai-interview-officer-team --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Ops Ai Interview Officer Team?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/whyzsm-ops-ai-interview-officer-team)More formats (shields.io, HTML) on the badges page.
---
name: ops-ai-interview-officer-team
description: "AI面谈官。用于提供九大智能面谈大纲与线上实时指引,基于云录制自动生成结构化纪要与待办。来源于 WorkBuddy 运营人力卡片,并转换为 Codex 可安装的专家入口格式。"
metadata:
source: "workbuddy-expert-center/运营人力/ops-ai-interview-officer"
workbuddy_card: "AI面谈官"
workbuddy_category: "运营人力"
---
# AI面谈官
Use this skill as the routing entry point for AI面谈官 work. It packages the WorkBuddy 运营人力 expert card into a Codex skill entry that can live in this repository without installing WorkBuddy.
## Workflow
1. Read `references/guide.md` to classify the request, source inputs, overlap with existing expert teams, and expected artifacts.
2. Use the narrowest relevant capability module from the guide. For full-package requests, follow `references/workflow.md` in order.
3. Ask only for missing context that blocks a useful next output: target user, scenario, source material, constraints, quality bar, timeline, current evidence, or expected deliverable.
4. Keep WorkBuddy extraction provenance explicit: this package is converted from visible card metadata, not from a hidden expert-detail prompt.
5. Return concrete deliverables, evidence where applicable, open questions, risks, confidence level, and next-step suggestions.
## Source Capability Modules
- `ops-ai-interview-officer-intake`
- `ops-ai-interview-officer-strategy`
- `ops-ai-interview-officer-execution`
- `ops-ai-interview-officer-quality`
- `ops-ai-interview-officer-measurement`
- `ops-ai-interview-officer-handoff`
## Output
Produce only the deliverables relevant to the request. For a full AI面谈官 package, assemble the output set described in `references/workflow.md`.
Is this your skill, or is something wrong with this listing? . Author removals are honored within 72 hours.
No comments yet. Be the first to comment!