复制安装命令
用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。
复制前请先查看来源、License 和安全提示。
Put your AI agent on the growth team.
用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。
复制前请先查看来源、License 和安全提示。
来源文件:README.md
Put your AI agent on the growth team.
Research customers and competitors, analyze what is working, create the next campaign, and learn from the result. Goose Skills gives Claude Code, Cursor, Codex, and other coding agents ready-to-use workflows for ads, social media, content, competitive intelligence, SEO, lead generation, and GTM.
Browse all skills at https://skills.gooseworks.ai
Works with Claude Code · Cursor · Codex
Paste this into your coding agent (Claude Code, Cursor, or Codex) and it'll set everything up:
Install the Gooseworks skills:
In the terminal, run `npx gooseworks install --all`.
Then run `npx gooseworks login` and it'll open a browser to sign in and set up the tools, then confirm it worked.
The skills can be used with /gooseworks <prompt>
Run this command in a terminal first:
npx gooseworks install --all
Then authenticate:
npx gooseworks login
Then make sure you're working inside a local folder on your machine, and then you can use the skills in Cowork like this:
Use /gooseworks skill to generate some ad creatives
Prefer to run it yourself? Use the command directly:
npx gooseworks install --all # All detected agents
This gives your coding agent access to the full catalog of 200+ skills. After installing, just ask your agent to use any skill by name.
If you want a cloud-based AI coworker that already knows all these skills and more, sign up to Gooseworks
The Brand Growth collection is a curated path through the normal Goose Skills catalog for consumer and ecommerce brand work. It is not a separate package or command: install GooseWorks once, then ask /gooseworks for the outcome you need.
| Stage | What your agent can do | Example skills |
|---|---|---|
| Research | Understand the brand, customers, competitors, audiences, creators, trends, comments, and product demand | brand-research, audience-research, comment-mining, competitor-social-research, influencer-prospecting, trend-discovery, product-demand-research |
| Analyze | Diagnose ads, creator profiles, transcripts, policy risk, landing-page message match, and unusual social performance | competitor-ad-intelligence, creator-profile-teardown, transcript-intelligence, meta-ads-analyzer, meta-ad-policy-checker, ad-to-landing-page-auditor, outlier-post-finder |
| Create | Repurpose research, remix graphic ads, make product photography and social graphics, and animate static images | content-repurposing, remix-graphic-ad-from-reference, product-photoshoot, goose-graphics, animate-image |
| Learn and iterate | Bring results back into research and analysis, then decide the next test | Re-run the relevant analysis skill with current performance and audience evidence |
ScrapeCreators powers structured public social and ad-library research behind several workflows. Signed-in GooseWorks users access it through the managed first-party proxy and do not need a separate ScrapeCreators key. The user-facing skills turn that source data into a brief, shortlist, analysis, or recommendation instead of returning raw API output.
Browse the Brand Growth collection
After installation, start with:
/gooseworks onboard me
The agent will collect the useful company context for future growth work and finish by asking what you want to do first. Existing users can skip onboarding and keep using /gooseworks exactly as they do today.
npx gooseworks search "reddit scraping" # Search the skill catalog
npx gooseworks credits # Check your credit balance
npx gooseworks update # Update to latest skill version
200+ skills across the growth stack, grouped by focus area:
| Category | What's inside |
|---|---|
| Ads | Research, build, and analyze paid campaigns across Meta and Google |
| SEO | Keyword research, content gaps, SERP analysis, technical audits |
| Lead generation | Find, enrich, and qualify prospects for your pipeline |
| Outreach | Draft, personalize, and run outbound across email and social |
| Content | Blog posts, social content, carousels, video scripts, newsletters |
| Research | Company, market, and prospect deep-dives |
| Competitive intel | Track competitor pricing, launches, positioning, and ads |
| Monitoring | Watch for mentions, signals, and changes across the web |
| Social | Scrape and analyze social platforms and audiences |
| Brand | Voice, positioning, and visual brand assets |
Browse and search every skill at skills.gooseworks.ai.
After installing, just ask your coding agent naturally:
"/gooseworks Generate static ad creatives for my brand"
"/gooseworks Use the reddit-post-finder skill to search r/startups"
"/gooseworks Use the apollo-lead-finder skill to find CTOs at AI companies"
"/gooseworks Use the competitor-intel skill to research Acme Corp"
"/gooseworks Use the goose-graphics skill to create a LinkedIn carousel about our launch"
Your agent will search the GooseWorks catalog, download the skill, and run it automatically.
git clone https://github.com/gooseworks-ai/goose-skills.git
cd goose-skills
node scripts/validate-skills.js # Validate SKILL.md + skill.meta.json contract
node scripts/build-index.js # Generate skills-index.json
node bin/goose-skills.js list # Test locally
Each skill directory must include:
SKILL.md — Skill documentation and usage guideskill.meta.json — Machine-readable metadataskill.meta.json fields:
| Field | Required | Description |
|---|---|---|
slug | Yes | Unique kebab-case identifier |
category | Yes | capabilities, composites, or playbooks |
tags | Yes | String array of category tags |
installation.base_command | Yes | Install command |
installation.supports | Yes | Array: claude, codex, cursor |
features | No | Feature flags |
github_url | No | Source repository URL |
author | No | Skill author |
example_prompt | No | Copyable prompt shown in the catalog and docs for trying the skill |
These skills run inside your coding agent, so it's worth knowing exactly what they do:
SKILL.md instructions and all scripts — lives in this repo under the MIT license. The gooseworks CLI fetches skills at runtime so recipes stay current, but the source you'd run is right here to read, diff, or pin before you run it./tmp/gooseworks-scripts/, never into your project directory. Only API requests go through GooseWorks servers; review any script before letting your agent run it.SKILL.md to tune that behavior.~/.gooseworks/credentials.json (file mode 0600). Third-party provider keys (Apify, Apollo, etc.) are held server-side — your token never touches them. All network calls are HTTPS.gooseworks install --mcp.Found something that looks off? Open an issue — we'd rather fix it in public.
MIT — see LICENSE for details.
The skill files and CLI in this repository are MIT-licensed. The GooseWorks API they connect to is a separate paid service governed by its own terms.
Built by GooseWorks
name: reddit-post-finder
description: Scrape and search Reddit posts using Apify. Use when you need to find Reddit discussions, track competitor mentions, monitor product feedback, discover pain points, or analyze subreddit content. Supports keyword filtering, time-based searches, and subreddit-specific queries.Scrape Reddit posts and comments using the Apify trudax/reddit-scraper-lite actor.
Requires APIFY_API_TOKEN env var (or --token flag).
# Top posts from r/growthhacking in last week
python3 skills/reddit-post-finder/scripts/search_reddit.py \
--subreddit growthhacking --days 7 --sort top --time week
# Hot posts from multiple subreddits
python3 skills/reddit-post-finder/scripts/search_reddit.py \
--subreddit "growthhacking,gtmengineering" --days 7 --sort hot
# Keyword-filtered competitor tracking
python3 skills/reddit-post-finder/scripts/search_reddit.py \
--subreddit LLMDevs \
--keywords "Langfuse,Arize,Langsmith" \
--days 30
# Human-readable summary table
python3 skills/reddit-post-finder/scripts/search_reddit.py \
--subreddit growthhacking --days 7 --output summary
https://www.reddit.com/r/growthhacking/top/?t=week)trudax/reddit-scraper-lite actor via REST API| Flag | Default | Description |
|---|---|---|
--subreddit | required | Subreddit name(s), comma-separated |
--keywords | none | Keywords to filter (comma-separated, OR logic) |
--days | 30 | Only include posts from the last N days |
--max-posts | 50 | Max posts to scrape per subreddit |
--sort | top | Sort: hot, top, new, rising |
--time | week | Time window for top sort: hour, day, week, month, year, all |
--output | json | Output format: json or summary |
--token | env var | Apify token (prefer APIFY_API_TOKEN env var) |
--timeout | 300 | Max seconds to wait for the Apify run |
Small or low-traffic subreddits (e.g. r/gtmengineering) may return zero posts with --sort hot because the hot feed is nearly empty. Use --sort top --time week (or month) instead — this scrapes the top-ranked posts over the time window and reliably returns results.
If calling the Apify API directly (e.g. via curl), note these required fields:
{
"startUrls": [{"url": "https://www.reddit.com/r/growthhacking/top/?t=week"}],
"maxItems": 50
}
Key notes for trudax/reddit-scraper-lite:
startUrls with full Reddit URLs (not a searches array for subreddit browsing)/top/?t=week), not separate input fieldsstartUrls and maxItems are confirmed working input fieldsproxyConfiguration, scrollTimeout, or searchTypeOutput fields:
dataType — "post" or "comment"title — Post titlebody — Post body textcommunityName — Subreddit name (without r/ prefix)upVotes — Number of upvotesnumberOfComments — Comment counturl — Full URL to the postcreatedAt — ISO timestamp of when the post was createdpython3 skills/reddit-post-finder/scripts/search_reddit.py \
--subreddit "LLMDevs,MachineLearning,LocalLLaMA" \
--keywords "Langfuse,Arize,Weights & Biases,Langsmith,Braintrust" \
--days 30 --sort top --time month
python3 skills/reddit-post-finder/scripts/search_reddit.py \
--subreddit LLMDevs \
--keywords "frustrating,difficult,hard to,wish there was,better way" \
--days 30
python3 skills/reddit-post-finder/scripts/search_reddit.py \
--subreddit "LLMDevs,MachineLearning" \
--keywords "YourProductName" \
--days 7 --sort new
When presenting Reddit results to the user, always include the original post URL for every post. This is critical for allowing users to read the full discussion, comments, and context. Never return a summary table without links.
Posts are returned as JSON array sorted by upvotes. Each post has:
{
"dataType": "post",
"title": "Post title",
"body": "Post body...",
"communityName": "growthhacking",
"upVotes": 42,
"numberOfComments": 15,
"createdAt": "2026-02-18T12:00:00.000Z",
"url": "https://reddit.com/r/..."
}
See references/apify-config.md for detailed API configuration, token setup, and rate limits.
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