技能详情（站内镜像，无评论）
许可证：MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本：v3.0.0
统计：⭐ 0 · 236 · 2 current installs · 2 all-time installs
⭐ 0
安装量（当前） 2
🛡 VirusTotal ：良性 · OpenClaw ：可疑
Package：agistack/interview
安全扫描（ClawHub）
- VirusTotal ：良性
- OpenClaw ：可疑
OpenClaw 评估
The skill's high-level claims mostly match benign local story/research tooling, but the implementation and SKILL.md overclaim features (many referenced scripts/files are missing) and paths are slightly inconsistent — so the package is incomplete and its capabilities are unclear.
目的
The name/description (interview prep, company research, story building, mock interviews, salary prep, follow-ups) aligns with the included scripts that build stories and scaffold company research. However the SKILL.md references many additional scripts (mock_interview.py, prep_salary.py, draft_followup.py, analyze_role.py, identify_gaps.py, log_feedback.py) and multiple references/*.md files that are not present in the bundle. That means the s…
说明范围
Runtime instructions and scripts operate entirely locally and only write/read JSON under a designated interview memory directory. There are no network calls, no external endpoints, and no environment variables accessed. Minor inconsistency: SKILL.md states data is stored under memory/interview/, while scripts use an absolute path under ~/.openclaw/workspace/memory/interview. The instructions also reference many missing scripts and reference do…
安装机制
No install spec is provided (instruction-only skill with a couple of small Python scripts). Nothing is downloaded or written outside the normal workspace path by an installer.
证书
No environment variables, credentials, or external config paths are requested. The scripts only use the user's home directory to store files; this is proportionate for a local interview prep tool.
持久
The skill does not request always:true, does not modify other skills, and does not require elevated privileges. It writes its own data into a hidden workspace directory under the user's home, which is expected for a local-memory feature.
安装（复制给龙虾 AI）
将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「Interview」。简介：Interview preparation system with company research, story building, and mock in…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/agistack/interview/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
---
name: interview
description: Interview preparation system with company research, story building, and mock interview practice. Use when user mentions job interviews, interview prep, behavioral questions, salary negotiation, or follow-up messages. Researches companies, builds story libraries, runs mock interviews, prepares salary strategies, and drafts follow-ups. NEVER guarantees job offers.
---
# Interview
Interview mastery system. Preparation that wins offers.
## Critical Privacy & Safety
### Data Storage (CRITICAL)
- **All interview data stored locally only**: `memory/interview/`
- **No external job platforms** connected
- **No application tracking systems** integrated
- **No sharing** of interview content
- User controls all data retention and deletion
### Safety Boundaries
- ✅ Research companies and roles
- ✅ Build story libraries from experience
- ✅ Run mock interviews with feedback
- ✅ Prepare salary negotiation strategies
- ❌ **NEVER guarantee** job offers
- ❌ **NEVER provide** false information
- ❌ **NEVER replace** genuine preparation
### Data Structure
Interview data stored locally:
- `memory/interview/research.json` - Company research briefs
- `memory/interview/stories.json` - Story library
- `memory/interview/practice.json` - Mock interview records
- `memory/interview/salary.json` - Salary research and strategies
- `memory/interview/feedback.json` - Post-interview notes
## Core Workflows
### Research Company
```
User: "Research Acme Corp for my interview Friday"
→ Use scripts/research_company.py --company "Acme Corp" --role "Product Manager"
→ Generate comprehensive research brief with talking points
```
### Build Story
```
User: "Help me build a story about the project failure"
→ Use scripts/build_story.py --situation "project-failure" --lesson "learned"
→ Structure STAR format story with specific details
```
### Mock Interview
```
User: "Run a mock interview for PM role"
→ Use scripts/mock_interview.py --role "Product Manager" --level senior
→ Ask realistic questions, provide honest feedback
```
### Prepare Salary
```
User: "How should I handle the salary question?"
→ Use scripts/prep_salary.py --role "Product Manager" --location "SF"
→ Research market data, prepare negotiation strategy
```
### Draft Follow-up
```
User: "Draft thank you email for today's interview"
→ Use scripts/draft_followup.py --interview "INT-123" --tone professional
→ Generate specific, memorable follow-up message
```
## Module Reference
- **Company Research**: See [references/research.md](references/research.md)
- **Story Building**: See [references/stories.md](references/stories.md)
- **Mock Interviews**: See [references/mock-interviews.md](references/mock-interviews.md)
- **Salary Negotiation**: See [references/salary.md](references/salary.md)
- **Difficult Questions**: See [references/difficult-questions.md](references/difficult-questions.md)
- **Follow-up Strategy**: See [references/followup.md](references/followup.md)
- **Handling Rejection**: See [references/rejection.md](references/rejection.md)
## Scripts Reference
| Script | Purpose |
|--------|---------|
| `research_company.py` | Generate company research brief |
| `build_story.py` | Build STAR format stories |
| `mock_interview.py` | Run practice interview |
| `prep_salary.py` | Prepare salary strategy |
| `draft_followup.py` | Draft follow-up messages |
| `analyze_role.py` | Analyze job description |
| `identify_gaps.py` | Identify experience gaps |
| `log_feedback.py` | Log post-interview feedback |