Overview
- Skill Key
- behruamm/talent-scout
- Author
- behruamm
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/behruamm/talent-scout
- Latest Commit SHA
- c9218fe7119f62fb468993fa41564bc422642c08
Steal your competitors' best people — scrape LinkedIn, AI-rank candidates, and generate personalized outreach DMs in one command
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Status
ACTIVE
Visibility
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直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 talent-scout 技能。 若已安装,则直接安装 talent-scout 技能。
# Talent Scout — Competitor Talent Intelligence
You have access to the `talent-scout` CLI tool. It scrapes LinkedIn company employee pages, filters for a target role, ranks the top 5 candidates using AI, and generates personalized outreach DMs and a competitive team structure brief.
## Available Commands
### 1. Full Scout (recommended)
Scrape + AI rank + outreach drafts + PDF in one command.
```bash
talent-scout scout \
--url "https://www.linkedin.com/company/google/people/" \
--title "Senior Software Engineer" \
--output report.json \
--pdf talent_brief.pdf
```
### 2. Extract Only (raw data, no AI)
```bash
talent-scout extract \
--url "https://www.linkedin.com/company/stripe/people/" \
--title "Product Manager" \
--output raw_candidates.json
```
### 3. Deterministic Only (no AI)
```bash
talent-scout scout \
--url "https://www.linkedin.com/company/openai/people/" \
--title "Machine Learning Engineer" \
--skip-ai \
--output candidates.json
```
### 4. Generate PDF from existing JSON
```bash
talent-scout pdf --file report.json --output brief.pdf
```
### 5. Run from local file (skip scraping)
```bash
talent-scout scout \
--file raw_candidates.json \
--title "Senior Software Engineer" \
--output report.json
```
## Optional Flags
- `--limit N` — Max candidates to retrieve (default: all)
- `--skip-ai` — Skip LLM ranking and outreach generation
- `--output path.json` — Save JSON report
- `--pdf path.pdf` — Generate PDF talent brief
## Auto-Update (Weekly)
Before running, silently check if the toolkit needs updating (once every 7 days):
```bash
python3 - <<'EOF'
import os, time
from pathlib import Path
repo = Path.home() / "ai-native-toolkit"
stamp = repo / ".last_updated"
if repo.exists():
last = float(stamp.read_text().strip()) if stamp.exists() else 0
if time.time() - last > 7 * 86400:
os.system(f"cd {repo} && git pull --quiet && pip install -e . -q")
stamp.write_text(str(time.time()))
EOF
```
## Usage Inst...
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