Tmux
trpc-group/trpc-agent-go
Remote-control tmux sessions for interactive CLIs by sending keystrokes and scraping pane output.
Extract structured data from web pages using AI. An agent skill from gooseworks-ai/goose-skills.
Install Extract Webpage Data
$ npx skills add gooseworks-ai/goose-skills --skill extract-webpage-data -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install gooseworks-ai/goose-skills extract-webpage-data --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/research-tools/capabilities/extract-webpage-data .claude/skills/extract-webpage-data && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "extract-webpage-data" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/research-tools/capabilities/extract-webpage-data into .claude/skills/extract-webpage-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "extract-webpage-data", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/gooseworks-ai/goose-skills/tree/main/skills/research-tools/capabilities/extract-webpage-dataType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add gooseworks-ai/goose-skills --skill extract-webpage-data -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install gooseworks-ai/goose-skills extract-webpage-data --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/research-tools/capabilities/extract-webpage-data .agents/skills/extract-webpage-data && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "extract-webpage-data" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/research-tools/capabilities/extract-webpage-data into .agents/skills/extract-webpage-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "extract-webpage-data", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gooseworks-ai/goose-skills --skill extract-webpage-data -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install gooseworks-ai/goose-skills extract-webpage-data --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/research-tools/capabilities/extract-webpage-data .cursor/skills/extract-webpage-data && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "extract-webpage-data" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/research-tools/capabilities/extract-webpage-data into .cursor/skills/extract-webpage-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "extract-webpage-data", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/gooseworks-ai/goose-skills.git --path skills/research-tools/capabilities/extract-webpage-data--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add gooseworks-ai/goose-skills --skill extract-webpage-data -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install gooseworks-ai/goose-skills extract-webpage-data --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/research-tools/capabilities/extract-webpage-data .gemini/skills/extract-webpage-data && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "extract-webpage-data" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/research-tools/capabilities/extract-webpage-data into .gemini/skills/extract-webpage-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "extract-webpage-data", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install gooseworks-ai/goose-skills extract-webpage-dataInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add gooseworks-ai/goose-skills --skill extract-webpage-data -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/research-tools/capabilities/extract-webpage-data .github/skills/extract-webpage-data && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "extract-webpage-data" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/research-tools/capabilities/extract-webpage-data into .github/skills/extract-webpage-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "extract-webpage-data", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gooseworks-ai/goose-skills --skill extract-webpage-data -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install gooseworks-ai/goose-skills extract-webpage-data --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/research-tools/capabilities/extract-webpage-data .opencode/skills/extract-webpage-data && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "extract-webpage-data" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/research-tools/capabilities/extract-webpage-data into .opencode/skills/extract-webpage-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "extract-webpage-data", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
extract-webpage-data- GitHub stars
- 1.2k
- Used in
- 1 other repo
- Token cost
- ~1.9k tokens
- SKILL.md length
- 515 words
- Files
- 2
- Skills in repo
- 273
- Repo updated
- First seen
- Licence
- MIT
At a glance
Extract structured data from web pages using AI. An agent skill from gooseworks-ai/goose-skills.
- Tasks that involve Web scraping
- SKILL.md covers Setup, When to Use, How It Works and Usage, plus 5 more sections
- Calls curl, python3 and npx; reaches api.gooseworks.ai; needs GOOSEWORKS_API_KEY
What it does
Extract Webpage Data is an agent skill from gooseworks-ai/goose-skills. Extract structured data from web pages using AI
Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `skill.meta.json`).
It sits in Data & Analytics, covering Web scraping. The repository describes itself as: Library of Growth & GTM skills + data APIs for Claude Code, Codex, Cursor to run ads, social, content, lead gen, seo and data scraping. The licence is MIT.
When your agent uses it
- Tasks that involve Web scraping
Example prompts
- “/extract-webpage-data”
Requirements
- Python 3
- Node.js
- A credential in GOOSEWORKS_API_KEY
What it can do on your machine
Read from SKILL.md and the folder at commit c650c6d. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
curlpython3npx
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
api.gooseworks.ai
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
GOOSEWORKS_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Extract Webpage Data loads about 1.9k tokens when it runs. Until then it costs about 17 tokens; SKILL.md has 515 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from gooseworks-ai/goose-skills at commit c650c6d, republished under its MIT licence (© gooseworks-ai). 515 words, ~1,857 tokens.
Download SKILL.mdSave it as
.claude/skills/extract-webpage-data/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- extract-webpage-data
- description
- Extract structured data from web pages using AI
- source
- orthogonal
Extract Webpage Data
Setup
Read your credentials from ~/.gooseworks/credentials.json:
export GOOSEWORKS_API_KEY=$(python3 -c "import json;print(json.load(open('$HOME/.gooseworks/credentials.json'))['api_key'])")
export GOOSEWORKS_API_BASE=$(python3 -c "import json;print(json.load(open('$HOME/.gooseworks/credentials.json')).get('api_base','https://api.gooseworks.ai'))")If ~/.gooseworks/credentials.json does not exist, tell the user to run: npx gooseworks login
All endpoints use Bearer auth: -H "Authorization: Bearer $GOOSEWORKS_API_KEY"
Extract structured data from any web page using AI. Turn messy HTML into clean, organized data.
When to Use
- User wants to extract specific data from a website
- User asks to scrape information from a page
- User needs structured data from unstructured content
- User wants to pull product info, contact details, etc.
- Converting web content to usable data
How It Works
Uses Olostep, Scrapegraph, or Riveter APIs for AI-powered data extraction.
Usage
Simple Scrape with Olostep
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"olostep","path":"/v1/scrapes","body":{"url_to_scrape":"https://example.com/products"}}'AI-Powered Extraction with Scrapegraph
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"scrapegraph","path":"/v1/smartscraper","body":{"website_url":"https://example.com/team","user_prompt":"Extract all team members with their names, titles, and LinkedIn URLs"}}'Schema-Based Extraction with Riveter
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"riveter","path":"/v1/scrape","body":{"url":"https://example.com","schema":{"name":"string","price":"number","description":"string"}}}'Get AI Answer from Web
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"olostep","path":"/v1/answers","body":{"task":"Find the pricing for Notion Teams plan from their website"}}'Crawl Multiple Pages
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"olostep","path":"/v1/crawls","body":{"start_url":"https://example.com","max_pages":10}}'Parameters
Olostep Scrape
- url_to_scrape (required) - URL to scrape
- formats - Output formats (markdown, html, text)
Scrapegraph
- website_url (required) - URL to scrape
- user_prompt (required) - Natural language description of what to extract
Riveter
- url (required) - URL to scrape
- schema - JSON schema defining the data structure to extract
Olostep Answer
- task (required) - Natural language task/question
Response
Olostep Response
Returns a scrape object:
- id (string) - Scrape ID (e.g.,
scrape_z926lxxon3) - result.markdown_content (string|null) - Page content as markdown
- result.html_content (string|null) - Raw HTML (if requested via
formats) - result.text_content (string|null) - Plain text (if requested)
- result.markdown_hosted_url (string|null) - S3 URL for large content
- result.links_on_page (array) - Links found on the page
- result.screenshot_hosted_url (string|null) - Screenshot URL (if requested)
- result.page_metadata (object) -
status_codeof the page - credits_consumed (integer) - Credits used for this scrape
Async crawls: POST /v1/crawls returns an id. Poll with GET /v1/crawls/{id} until complete.
Scrapegraph Response
Returns structured extraction result:
- request_id (string) - Unique request identifier
- status (string) -
completedorpending - result (object) - AI-extracted data matching your prompt (dynamic keys)
- error (string) - Empty on success, error message on failure
Note: For large pages, the POST may return status: "pending". Poll with GET /v1/smartscraper/{request_id} until status is completed.
Show full SKILL.md (210 more words)Show less
Riveter Response
Returns scrape result:
- request_status (string) -
successorerror - message (string) - Human-readable status
- text (string) - Extracted page text content
- url (string) - URL that was scraped
- status_code (integer) - HTTP status of the page
- run_key (string) - Unique run identifier
- base_url_for_links (string) - Base URL for resolving relative links
- riveter_app_link (string) - Link to view run in Riveter dashboard
- credit_used (integer) - Credits consumed
Examples
User: "Get all the product names and prices from this page"
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"scrapegraph","path":"/v1/smartscraper","body":{"website_url":"https://example.com/products","user_prompt":"Extract all products with name, price, and description"}}'User: "Scrape the team page and get everyone's info"
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"scrapegraph","path":"/v1/smartscraper","body":{"website_url":"https://example.com/about/team","user_prompt":"Extract team members: name, role, bio, photo URL, LinkedIn"}}'User: "What are Stripe's API pricing details?"
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"olostep","path":"/v1/answers","body":{"task":"Find Stripe API pricing breakdown from stripe.com/pricing"}}'User: "Get all blog post titles and dates from this blog"
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"riveter","path":"/v1/scrape","body":{"url":"https://blog.example.com","schema":{"posts":[{"title":"string","date":"string","url":"string"}]}}}'Error Handling
- 504 - Olostep timeout on slow pages — retry or try a simpler URL
- 400 - Missing required parameters (
url_to_scrapefor Olostep,website_url+user_promptfor Scrapegraph,urlfor Riveter) - Scrapegraph returns
errorfield in response body — check it even on 200 status - Riveter returns
request_status: "error"with details inmessage - Some sites block automated scraping — try a different API if one fails
Tips
- Scrapegraph is best for natural language extraction
- Riveter is best when you know the exact schema you want
- Olostep is great for general scraping and AI answers
- For dynamic sites (JavaScript-heavy), these tools handle rendering
- Be specific in your prompts for better extraction results
- Some sites may block automated access
© gooseworks-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file in skills/research-tools/capabilities/extract-webpage-data of gooseworks-ai/goose-skills.
- SKILL.md
- skill.meta.json
Open the folder on GitHubat commit c650c6d
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in gooseworks-ai/goose-skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Extract Webpage Data next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Extract Webpage Data this skillgooseworks-ai/goose-skills | 1.2k | 1 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Tmuxtrpc-group/trpc-agent-go | 1.9k | 23 repos | ~868 | Automated safety check: Pass | Apache-2.0 | |
| Ketch1broseidon/ketch | 702 | 1 repos | ~3.9k | Automated safety check: Pass | MIT | |
| Boss Zhipin Scrapereatmoreduck/boss-zhipin-scraper | 1.5k | — | ~2.6k | Automated safety check: Pass | MIT | |
| Crawl4AI Web Scrapingsmallnest/goclaw | 599 | 1 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Axyusukebe/ax | 719 | 1 repos | ~918 | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Extract Webpage Data
What does Extract Webpage Data do?
Extract structured data from web pages using AI. An agent skill from gooseworks-ai/goose-skills. Extract Webpage Data is an agent skill from gooseworks-ai/goose-skills.
When should I use Extract Webpage Data?
Extract Webpage Data fits situations like: tasks that involve Web scraping.
How do I install Extract Webpage Data in Claude Code?
Run `npx skills add gooseworks-ai/goose-skills --skill extract-webpage-data -a claude-code`. Or copy the skill folder (skills/research-tools/capabilities/extract-webpage-data in gooseworks-ai/goose-skills) into .claude/skills/extract-webpage-data in your project. Claude Code loads it when a task matches its description.
How do I install Extract Webpage Data in Codex?
Run `npx skills add gooseworks-ai/goose-skills --skill extract-webpage-data -a codex`. Or copy the skill folder (skills/research-tools/capabilities/extract-webpage-data in gooseworks-ai/goose-skills) into .agents/skills/extract-webpage-data in your project. Codex loads it when a task matches its description.
Can I use Extract Webpage Data in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add gooseworks-ai/goose-skills --skill extract-webpage-data -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/extract-webpage-data, .gemini/skills/extract-webpage-data, .github/skills/extract-webpage-data and .opencode/skills/extract-webpage-data in your project.
What does Extract Webpage Data need to run?
Going by SKILL.md and its folder, Extract Webpage Data needs the command-line tools its instructions call (curl, python3 and npx) and credentials named GOOSEWORKS_API_KEY. Our summary lists: Python 3; Node.js; A credential in GOOSEWORKS_API_KEY.
Does Extract Webpage Data access the network?
SKILL.md names 1 domain. In commands or code: api.gooseworks.ai; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Is Extract Webpage Data safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Extract Webpage Data use?
Extract Webpage Data is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Extract Webpage Data use?
About 1.9k tokens (SKILL.md is roughly 7.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Extract Webpage Data?
Skills that share tags, products or a category with Extract Webpage Data: Tmux (trpc-group/trpc-agent-go, 1.9k stars), Ketch (1broseidon/ketch, 702 stars), Boss Zhipin Scraper (eatmoreduck/boss-zhipin-scraper, 1.5k stars) and Crawl4AI Web Scraping (smallnest/goclaw, 599 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Extract Webpage Data?
gooseworks-ai (a GitHub organization) maintains it in gooseworks-ai/goose-skills, which has 1,240 GitHub stars. The repository holds 273 skills in this directory. The repository was last updated on October 8, 2026.
Source: gooseworks-ai/goose-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.