菜单
Competitor intelligence system. Track competitors across Reddit, Twitter/X, and LinkedIn. Run one-time deep research to create competitor profiles, then automate daily/weekly monitoring with consolidated reports and actionable signals. Reports delivered as markdown files and via email.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/gooseworks-ai/gooseworks-skills --skill competitor-intel命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Search LinkedIn posts by keywords using Crustdata API directly, deduplicate and sort by engagement. Outputs to CSV or JSON. Use when researching LinkedIn content around specific topics.
Crawl a website's sitemap and blog index to build a complete content inventory. Lists every page with URL, title, publish date, content type, and topic cluster. Groups content by category and topic. Optionally deep-reads top N pages for quality analysis and funnel stage tagging. Use before SEO audits, content gap analysis, or brand voice extraction.
Mine the highest-converting ad angles from customer reviews, Reddit complaints, support tickets, and competitor ads. Extracts actual pain language, competitor weaknesses, and outcome phrases that real buyers use. Outputs a ranked angle bank with proof quotes and recommended ad formats per angle.
基于 SOC 职业分类
正在显示 SKILL.md
| name | competitor-intel |
| description | Competitor intelligence system. Track competitors across Reddit, Twitter/X, and LinkedIn. Run one-time deep research to create competitor profiles, then automate daily/weekly monitoring with consolidated reports and actionable signals. Reports delivered as markdown files and via email. |
Automated competitor monitoring and intelligence gathering system.
Important: Before running any competitor intel commands, ask the user which competitors they want to track. Do not assume or hardcode competitor names.
# Create a new competitor profile (agent-driven research)
python3 competitor-intel/scripts/setup_competitor.py --name "CompanyName" --website https://example.com --slug companyname
Then run an agent research session to populate the profile.
# Run daily signals collection (automated via cron)
python3 competitor-intel/scripts/run_daily.py
# Or for a specific competitor
python3 competitor-intel/scripts/run_daily.py --competitor <competitor-slug>
# Run weekly deep dive (Monday mornings)
python3 competitor-intel/scripts/run_weekly.py
# Generate daily or weekly report
python3 competitor-intel/scripts/generate_report.py --type daily --date 2026-02-21
python3 competitor-intel/scripts/generate_report.py --type weekly --date 2026-02-21
competitor-intel/competitors/[slug]/profile.md - Deep research profile per competitorcompetitor-intel/competitors/[slug]/snapshots/ - Point-in-time weekly snapshotscompetitor-intel/reports/ - Daily and weekly digest reportscompetitor-intel/raw-data/ - Raw JSON from Reddit/Twitter scrapescompetitor-intel/config.json - Global configurationCompetitors are configured per-project. Ask the user which competitors to track, then add them here:
| Competitor | Slug | Status |
|---|---|---|
| (ask user) | — | — |