producthunt-launches
Scrape Product Hunt daily/weekly/monthly/yearly leaderboard launches with full product details, maker profiles, and website contact info.
Skill by browser-act
Chalk Labs
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/browser-act-producthunt-launches
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: backend, data, sales, productivity
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 2
codeload.github.com· found in install commandproducthunt.com· found in code
Files it touches
~/.claude/skills/producthunt-launches
What's inside
- Skill name
producthunt-launches- Description
- Scrape Product Hunt daily/weekly/monthly/yearly leaderboard launches with full product details, maker profiles, and website contact info. Use when user mentions Product Hunt, producthunt, PH scraper, product hunt launches, product hunt leaderboard, scrape product hunt, product hunt data, PH daily launches, product hunt upvotes, product hunt maker info, extract product hunt, product hunt today, top products product hunt, product hunt archive, PH products, product hunt email extraction, product hunt contact info, producthunt.com scraping, get product hunt launches, product hunt API alternative. Also applies to: startup launch monitoring, new product discovery, maker/founder contact enrichment, product hunt lead generation, daily product hunt digest, competitive product tracking.
- License
- MIT
- Instructions
- 217 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (5)
- SKILL.md
- extract-launch-detail.py · scripts/
- extract-leaderboard.py · scripts/
- extract-maker-profile.py · scripts/
- extract-website-content.py · scripts/
SKILL.md (first lines)
# Product Hunt — Launch Data Extraction
> Input: date/period parameters → Output: structured product launch data with maker profiles and website contact info
## Language
All process output to user (progress updates, process notifications) follows the user's language.
## Objective
Extract complete product launch data from Product Hunt leaderboard pages, enriched with maker profile information and product website contact details.
## Prerequisites
- Browser session is open and can access producthunt.com
- Cloudflare challenge may appear on first visit; use `solve-captcha` or wait for auto-pass
## Pre-execution Checks
### 1. Tool Readiness
If browser-act has been confirmed available in the current session → skip this step.
Invoke `browser-act` via Skill tool to load usage. If installation or configuration issues arise, follow its guidance to resolve then retry.
### 2. Cloudflare Verification
Product Hunt uses Cloudflare protection. On first navigation:
1. Navigate to target URL
2. If page title shows "Just a moment..." → `wait stable --timeout 15000` then check title again
3. If still blocked → `solve-captcha`
4. Verify page loaded: title should contain "Product Hunt" or "Best of Product Hunt"
## Capability Components
> This Skill's operational boundary = what the user can manually do in their browser. It only reads data already displayed to the user on the page, never bypassing authentication or access controls. JS code is encapsulated in Python files under the `scripts/` directory, invoked via `eval "$(python scripts/xxx.py)"`. `$(...)` is bash syntax; use the bash tool for execution.
### DOM: Extract product list from leaderboard page
Navigate to the target leaderboard URL first, then extract:
`eval "$(python scripts/extract-leaderboard.py)"`
URL patterns (navigate to the appropriate one before extraction):
- Daily: `https://www.producthunt.com/leaderboard/daily/{YYYY}/{M}/{DD}/all`
- Weekly: `https://www.producthunt.com/leaderboard/weekly/{YYYY}/{week-number}/all`
- Monthly: `https://www.producthunt.com/leaderboard/monthly/{YYYY}/{M}/all`
- Yearly: `https://www.producthunt.com/leaderboard/yearly/{YYYY}/all`
Replace `all` with `featured` for featured-only products.
Output example:
```json
[
{
"rank": 1,
"name": "Product Name",
"tagline": "Short product description",
"categories": ["Productivity", "AI"],
"thumbnail": "https://ph-files.imgix.net/...",
"upvotes": 135,
"comments": 42,
"url": "https://www.producthunt.com/products/product-slug",
"slug": "product-slug"
}
]
```
### DOM: Extract launch detail page
Navigate to the launch page URL first (`https://www.producthunt.com/products/{slug}/launches/{launch-slug}`), then extract:
`eval "$(python scripts/extract-launch-detail.py)"`
To find the launch URL from a product page: navigate to `https://www.producthunt.com/products/{slug}` and look for links matching `/products/{slug}/launches/{launch-slug}`.
Output example:
```json
{
"name": "Product Name",
"tagline": "Short product tagline",
"description": "Full product description from OG meta",
"categories": ["Productivity", "Social Media"],
"images": ["https://ph-files.imgix.net/gallery1.png", "https://ph-files.imgix.net/gallery2.png"],
"websiteUrl": "https://product-website.com/?ref=producthunt",
"upvotes": 135,
"launchDate": "2025-05-27T07:26:33-07:00",
"makers": [{"href": "/@username", "name": "Maker Name"}],
"ogImage": "https://ph-files.imgix.net/og-image.png"
}
```
### DOM: Extract maker profile
Navigate to maker profile URL (`https://www.producthunt.com/@{username}`), then extract:
`eval "$(python scripts/extract-maker-profile.py)"`
Output example:
```json
{
"name": "Maker Name",
"slug": "@username",
"headline": "Creating SaaS Products",
"aboutText": "Bio text about the maker",
"links": ["https://twitter.com/username", "https://linkedin.com/in/username"],
"followers": 22,
"url": "https://www.producthunt.com/@username"
}
```
### DOM: Extract website email and content
Navigate to the product website URL, wait for load, then extract:
`eval "$(python scripts/extract-website-content.py)"`
Alternatively, use `stealth-extract` for faster extraction without a browser session:
`stealth-extract {website-url} --content-type markdown` then parse the markdown for email patterns.From browser-act/skills, MIT.
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Signals
- Stars
- 6,268
- Forks
- 330
- Open issues
- 9
- Last commit (this folder)
- Jun 12, 2026 (4 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/browser-act/skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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Cite this page
producthunt-launches skill. Agent Mart. https://agentmart.dev/skills/browser-act-producthunt-launches (last updated 2026-10-24)