Agent skill

Structured Scraping Riveter

by gooseworks-ai in gooseworks-ai/goose-skills

Web scraping with structured data extraction - define your output schema

MITAuto-check passedData & Analytics

Install Structured Scraping Riveter

skills CLI
$ npx skills add gooseworks-ai/goose-skills --skill structured-scraping-riveter -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install gooseworks-ai/goose-skills structured-scraping-riveter --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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/structured-scraping-riveter .claude/skills/structured-scraping-riveter && rm -rf skills-src

Use ~/.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/

Facts

Skill name
structured-scraping-riveter
GitHub stars
1.2k
Used in
1 other repo
Token cost
~1.5k tokens
SKILL.md length
504 words
Files
2
Skills in repo
273
Repo updated
First seen
Licence
MIT

At a glance

Web scraping with structured data extraction - define your output schema

  • Works in 4 steps: E-commerce Scraping: Extract product… → Job Listings: Gather job postings with… → News Aggregation: Extract articles with… → …
  • Tasks that involve Web scraping
  • SKILL.md covers Setup, Capabilities, Usage and Use Cases, plus 1 more section
  • Calls curl, python3 and npx; reaches api.gooseworks.ai; needs GOOSEWORKS_API_KEY

What it does

Structured Scraping Riveter is an agent skill from gooseworks-ai/goose-skills. Web scraping with structured data extraction - define your output schema

Its SKILL.md is about 1.5k 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

  • “/structured-scraping-riveter”

Requirements

  • Python 3
  • Node.js
  • A credential in GOOSEWORKS_API_KEY

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. E-commerce Scraping: Extract product data in consistent format
  2. Job Listings: Gather job postings with structured fields
  3. News Aggregation: Extract articles with title, date, content
  4. Price Monitoring: Track prices across competitor sites

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:

    • curl
    • python3
    • npx

    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

Structured Scraping Riveter loads about 1.5k tokens when it runs. Until then it costs about 25 tokens; SKILL.md has 504 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~25
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

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). 504 words, ~1,461 tokens.

Download SKILL.mdSave it as .claude/skills/structured-scraping-riveter/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
structured-scraping-riveter
description
Web scraping with structured data extraction - define your output schema
source
orthogonal

Riveter - Structured Web Scraping

Setup

Read your credentials from ~/.gooseworks/credentials.json:

bash
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"

Scrape web pages and extract data into your defined structure.

Capabilities

  • Scrape: Scrape a webpage and return the text content
  • Run: Copy link Define the structure of your output directly in the API request
  • Run data: Retrieve the processed data from a completed project run (free)
  • Run status: Check the current status of a project run (free)
  • Stop run: Stop a currently running project (free)

Usage

Scrape

Scrape a webpage and return the text content. This endpoint allows you to extract text content from any public webpage.

Parameters:

  • url* (string) - Example: "https://example.com"
  • proxy_country_code (string) - Optional two-character country code for proxy (e.g., 'us', 'gb', 'de')
  • skip_cache (boolean) - Default: false. Set to true to bypass cache and always fetch fresh content
bash
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/article"}}'
Run

Copy link Define the structure of your output directly in the API request. This endpoint allows you to define both your input data and output configuration in a single request.

Parameters:

  • input* (object) - The input object contains your source data: Keys are column/attribute names Values are arrays of strings (all arrays must be the same length) Maximum 1000 rows per request
  • output* (object) - The output object defines what data you want to extract: Keys are the names of attributes you want to extract Each attribute requires: prompt: Instructions for finding/extracting this data contexts: Array of input or other output attribute names this depends on. Optional Output Configuration Each output attribute can optionally include: format: Data type ('number', 'json', 'url', 'text', 'email', 'tag', 'date', 'boolean') format_details: Format-specific configuration (varies by format type). For json format, you can provide either a description (string) or a schema (JSON Schema object) or both. tools: Array of tools to use (['web_search', 'web_scrape', 'query_pdf', 'query_image']) max_tool_calls: Number of tool calls allowed (0-10) run_when: When to run this extraction ('always', 'any_filled', 'all_filled')
  • run_key (string) - Custom identifier for this run (optional, will be generated if not provided)
bash
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/run"}'
  "input": {
    "urls": ["https://example.com/products"]
  },
  "output": {
    "name": {"prompt": "Product name", "contexts": ["urls"]},
    "price": {"prompt": "Product price", "contexts": ["urls"], "format": "number"}
  }
}'
Show full SKILL.md (163 more words)Show less
Run data (free)

Retrieve the processed data from a completed project run

Parameters:

  • run_key* (string) - The run key (UUID) of the project run to retrieve data for
bash
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/run_data","query":{"run_key":"abc123"}}'
Run status (free)

Check the current status of a project run

Parameters:

  • run_key* (string) - The run key (UUID) of the project run to check
bash
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/run_status","query":{"run_key":"abc123"}}'
Stop run (free)

Stop a currently running project. This will halt all processing and mark the run as stopped. Behavior: If the run is already stopped or success, returns success with current status. If the run is in progress, stops all pending cells and marks the run as stopped. Stopped runs cannot be resumed

Parameters:

  • run_key* (string) - The run key (UUID) of the project run to stop
bash
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/stop_run","query":{"run_key":"abc123"}}'

Use Cases

  1. E-commerce Scraping: Extract product data in consistent format
  2. Job Listings: Gather job postings with structured fields
  3. News Aggregation: Extract articles with title, date, content
  4. Price Monitoring: Track prices across competitor sites

Discover More

For full endpoint details and parameters:

bash
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/search \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt":"riveter API endpoints"}' List all endpoints
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/details \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"riveter","path":"/v1/scrape"}'   # Get endpoint details

© 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/structured-scraping-riveter 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

Structured Scraping Riveter 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.

Structured Scraping Riveter compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Structured Scraping Riveter this skillgooseworks-ai/goose-skills1.2k1 repos~1.5kAutomated safety check: PassMIT
Tmuxtrpc-group/trpc-agent-go1.9k23 repos~868Automated safety check: PassApache-2.0
Ketch1broseidon/ketch7021 repos~3.9kAutomated safety check: PassMIT
Boss Zhipin Scrapereatmoreduck/boss-zhipin-scraper1.5k—~2.6kAutomated safety check: PassMIT
Crawl4AI Web Scrapingsmallnest/goclaw5991 repos~2.5kAutomated safety check: PassMIT
Axyusukebe/ax7191 repos~918Automated safety check: PassMIT

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Questions about Structured Scraping Riveter

What does Structured Scraping Riveter do?

Web scraping with structured data extraction - define your output schema. Structured Scraping Riveter is an agent skill from gooseworks-ai/goose-skills.

When should I use Structured Scraping Riveter?

Structured Scraping Riveter fits situations like: tasks that involve Web scraping.

How do I install Structured Scraping Riveter in Claude Code?

Run `npx skills add gooseworks-ai/goose-skills --skill structured-scraping-riveter -a claude-code`. Or copy the skill folder (skills/research-tools/capabilities/structured-scraping-riveter in gooseworks-ai/goose-skills) into .claude/skills/structured-scraping-riveter in your project. Claude Code loads it when a task matches its description.

How do I install Structured Scraping Riveter in Codex?

Run `npx skills add gooseworks-ai/goose-skills --skill structured-scraping-riveter -a codex`. Or copy the skill folder (skills/research-tools/capabilities/structured-scraping-riveter in gooseworks-ai/goose-skills) into .agents/skills/structured-scraping-riveter in your project. Codex loads it when a task matches its description.

Can I use Structured Scraping Riveter 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 structured-scraping-riveter -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/structured-scraping-riveter, .gemini/skills/structured-scraping-riveter, .github/skills/structured-scraping-riveter and .opencode/skills/structured-scraping-riveter in your project.

What does Structured Scraping Riveter need to run?

Going by SKILL.md and its folder, Structured Scraping Riveter 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 Structured Scraping Riveter 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 Structured Scraping Riveter 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 Structured Scraping Riveter use?

Structured Scraping Riveter 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 Structured Scraping Riveter use?

About 1.5k tokens (SKILL.md is roughly 5.8k 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 Structured Scraping Riveter?

Skills that share tags, products or a category with Structured Scraping Riveter: 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 Structured Scraping Riveter?

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.