New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Web Search

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

Search the web, platforms, and datasets. An agent skill from gooseworks-ai/goose-skills.

MITAuto-check passedProductivity & Automation

Install Web Search

skills CLI
$ npx skills add gooseworks-ai/goose-skills --skill web-search -a claude-code

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

GitHub CLI
$ gh skill install gooseworks-ai/goose-skills web-search --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/web-search .claude/skills/web-search && 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
web-search
GitHub stars
1.2k
Used in
1 other repo
Token cost
~4.2k tokens
SKILL.md length
558 words
Files
2
Skills in repo
273
Repo updated
First seen
Licence
MIT

At a glance

Search the web, platforms, and datasets. An agent skill from gooseworks-ai/goose-skills.

  • Works in 6 steps: Tavily — Comprehensive Web Search &… → Exa — Neural & Semantic Search → Andi — Fast Web Search → …
  • Asked to search
  • SKILL.md covers Setup, 1. Tavily — Comprehensive Web…, 2. Exa — Neural & Semantic… and 3. Andi — Fast Web Search, plus 5 more sections
  • Calls curl, python3 and npx; reaches api.gooseworks.ai; needs GOOSEWORKS_API_KEY

What it does

Web Search is an agent skill from gooseworks-ai/goose-skills. Search the web, platforms, and datasets. Use when asked to search, find, look up, research, or discover information from the web, YouTube, Amazon, eBay, news, academic sources, or any online platform.

Its SKILL.md is about 4.2k 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 Productivity & Automation, covering Web search. It works with YouTube. 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

  • Asked to search
  • Discover information from the web
  • Academic sources
  • Any online platform

Example prompts

  • “/web-search”

Requirements

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

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Tavily — Comprehensive Web Search & Research
  2. Exa — Neural & Semantic Search
  3. Andi — Fast Web Search
  4. Linkup — Question-Based Search with Sourced Answers
  5. Valyu — Web, Proprietary Datasets & News Search
  6. SearchAPI — Multi-Platform Search

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

Web Search loads about 4.2k tokens when it runs. Until then it costs about 53 tokens; SKILL.md has 558 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~53
When it runs · the whole SKILL.md, loaded when a task matches
~4.2k

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). 558 words, ~4,240 tokens.

Download SKILL.mdSave it as .claude/skills/web-search/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
web-search
description
Search the web, platforms, and datasets. Use when asked to search, find, look up, research, or discover information from the web, YouTube, Amazon, eBay, news, academic sources, or any online platform.
source
orthogonal

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"

Search the web, platforms, and proprietary datasets. Pick the best API for the task — or combine several for comprehensive results.

1. Tavily — Comprehensive Web Search & Research

Best for: General web search, deep research reports, site mapping, and crawling.

Search the web:

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":"tavily","path":"/search"}'
  "query": "latest developments in AI agents",
  "search_depth": "advanced",
  "include_answer": true,
  "max_results": 10
}'

Deep research (async — returns a report with citations):

bash
# Step 1: Start research task
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"tavily","path":"/research","body":{"input":"Compare AI agent frameworks for production use","model":"pro"}}'
# Step 2: Poll for results using request_id
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"tavily","path":"/research/{request_id}"}'

Map a website (discover all URLs):

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":"tavily","path":"/map","body":{"url":"https://docs.example.com","limit":200}}'

Crawl a website (extract content from multiple pages):

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":"tavily","path":"/crawl"}'
  "url": "https://docs.example.com",
  "max_depth": 3,
  "limit": 50
}'

Key parameters: search_depth (basic/fast/advanced/ultra-fast), topic (general/news), time_range (day/week/month/year), include_domains/exclude_domains, include_answer, include_raw_content, country.

Best for: Finding similar content, semantic/embeddings-based search, category-filtered search (people, companies), and deep research.

Neural web search:

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":"exa","path":"/search"}'
  "query": "startups building AI coding assistants",
  "numResults": 10,
  "type": "auto",
  "contents": {"text": true}
}'

Find similar pages:

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":"exa","path":"/findSimilar"}'
  "url": "https://example.com/article",
  "numResults": 10,
  "contents": {"text": true}
}'

Get a sourced AI answer:

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":"exa","path":"/answer","body":{"query":"What are the best practices for prompt engineering?"}}'

Get page contents:

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":"exa","path":"/contents","body":{"urls":["https://example.com"],"text":true,"summary":true}}'

Deep research (async):

bash
# Step 1: Create task
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"exa","path":"/research/v1","body":{"instructions":"Research the current state of AI coding assistants","model":"exa-research-pro"}}'
# Step 2: Poll with researchId
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"exa","path":"/research/v1/{researchId}"}'

Key parameters: type (auto/neural/fast/deep), category (people/company), includeDomains/excludeDomains, startPublishedDate/endPublishedDate, includeText/excludeText.

Best for: Quick, high-quality web search with intelligent ranking and instant answers. Low latency.

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":"andi","path":"/v1/search","query":{"q":"how%20does%20RAG%20work","depth":"deep","limit":"20"}}'

Key parameters: q (query), limit (1-100), depth (fast/deep), intent (NewsSearchIntent, VideoSearchIntent, ImageSearchIntent), dateRange (day/week/month/year), includeDomains/excludeDomains, country, language.

4. Linkup — Question-Based Search with Sourced Answers

Best for: Natural language questions, sourced answers with citations, structured output.

Search with sourced answer:

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":"linkup","path":"/search"}'
  "q": "What are the latest AI agent frameworks?",
  "depth": "deep",
  "outputType": "sourcedAnswer"
}'

Structured output search:

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":"linkup","path":"/search"}'
  "q": "Top 5 AI startups in 2025",
  "depth": "deep",
  "outputType": "structured",
  "structuredOutputSchema": {
    "type": "object",
    "properties": {
      "startups": {
        "type": "array",
        "items": {
          "type": "object",
          "properties": {
            "name": {"type": "string"},
            "description": {"type": "string"},
            "funding": {"type": "string"}
          }
        }
      }
    }
  }
}'

Key parameters: q (natural language question), depth (standard/deep), outputType (searchResults/sourcedAnswer/structured), fromDate/toDate, includeDomains/excludeDomains, maxResults.

Best for: Searching across web, academic/proprietary datasets, and news. AI-generated answers. Deep research tasks.

Web search:

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":"valyu","path":"/v1/search","body":{"query":"AI agent frameworks comparison","search_type":"web","max_num_results":10}}'

Academic/proprietary search:

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":"valyu","path":"/v1/search","body":{"query":"transformer architecture improvements","search_type":"proprietary"}}'

News search:

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":"valyu","path":"/v1/search","body":{"query":"OpenAI latest announcements","search_type":"news"}}'

AI-generated answer:

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":"valyu","path":"/v1/answer","body":{"query":"What are best practices for building AI agents?"}}'

Deep research (async):

bash
# Step 1: Create task
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"valyu","path":"/v1/deepresearch/tasks","body":{"query":"Comprehensive analysis of vector databases market","mode":"standard"}}'
# Step 2: Poll for status
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"valyu","path":"/v1/deepresearch/tasks/{id}/status"}'

Key parameters: search_type (web/proprietary/news), fast_mode, included_sources/excluded_sources, relevance_threshold, start_date/end_date, country_code.

Best for: Searching specific platforms — Amazon, eBay, Walmart, YouTube, Airbnb, TripAdvisor, app stores, and ad libraries (Meta, TikTok, Reddit, LinkedIn).

All SearchAPI calls use the same endpoint with different engine values:

Amazon product search:

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":"searchapi","path":"/api/v1/search","query":{"engine":"amazon_search","q":"wireless%20headphones"}}'

eBay search:

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":"searchapi","path":"/api/v1/search","query":{"engine":"ebay_search","q":"vintage%20watch"}}'

Walmart search:

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":"searchapi","path":"/api/v1/search","query":{"engine":"walmart_search","q":"laptop"}}'

YouTube search:

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":"searchapi","path":"/api/v1/search","query":{"engine":"youtube","q":"AI%20agents"}}'

YouTube video details / comments / transcripts:

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":"searchapi","path":"/api/v1/search","query":{"engine":"youtube_video","video_id":"dQw4w9WgXcQ"}}'
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"searchapi","path":"/api/v1/search","query":{"engine":"youtube_comments","video_id":"dQw4w9WgXcQ"}}'
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"searchapi","path":"/api/v1/search","query":{"engine":"youtube_transcripts","video_id":"dQw4w9WgXcQ"}}'

Airbnb search:

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":"searchapi","path":"/api/v1/search","query":{"engine":"airbnb","q":"Paris","adults":"2","check_in_date":"2025-06-01","check_out_date":"2025-06-07"}}'

TripAdvisor search:

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":"searchapi","path":"/api/v1/search","query":{"engine":"tripadvisor","q":"best%20restaurants%20NYC"}}'

Apple App Store:

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":"searchapi","path":"/api/v1/search","query":{"engine":"apple_app_store","term":"productivity"}}'

Ad library search (Meta, TikTok, Reddit, LinkedIn):

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":"searchapi","path":"/api/v1/search","query":{"engine":"meta_ad_library","q":"AI%20tools"}}'
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"searchapi","path":"/api/v1/search","query":{"engine":"tiktok_ads_library","q":"AI"}}'
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"searchapi","path":"/api/v1/search","query":{"engine":"reddit_ad_library","q":"software"}}'
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"searchapi","path":"/api/v1/search","query":{"engine":"linkedin_ad_library","q":"hiring"}}'

Social media profiles:

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":"searchapi","path":"/api/v1/search","query":{"engine":"tiktok_profile","username":"openai"}}'
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"api":"searchapi","path":"/api/v1/search","query":{"engine":"instagram_profile","username":"openai"}}'

Available engines: amazon_search, ebay_search, walmart_search, youtube, youtube_video, youtube_comments, youtube_transcripts, youtube_channel, youtube_channel_videos, airbnb, tripadvisor, apple_app_store, meta_ad_library, tiktok_ads_library, reddit_ad_library, linkedin_ad_library, tiktok_profile, instagram_profile.

Show full SKILL.md (204 more words)Show less

Tips

  • General web search: Start with Tavily (search_depth: "advanced") or Exa (type: "auto") for best relevance
  • Speed matters: Use Andi for fast results, Tavily ultra-fast for lowest latency
  • Sourced answers: Linkup and Valyu both generate answers with citations — Linkup is best for Q&A, Valyu for blending web + proprietary data
  • Academic/research data: Valyu's proprietary search type covers arxiv, pubmed, and academic datasets
  • News: Use Valyu (search_type: "news") or Tavily (topic: "news") for current events
  • Deep research: Tavily, Exa, and Valyu all offer async research tasks — Tavily for web-focused, Exa for comprehensive with citations, Valyu for web + academic mix
  • Find similar content: Exa's /findSimilar is unique — pass a URL and get semantically similar pages
  • Platform-specific search: SearchAPI is the only option for Amazon, eBay, Walmart, YouTube, Airbnb, TripAdvisor, and ad libraries
  • Domain filtering: Most APIs support include_domains/exclude_domains to scope results
  • Async patterns: Deep research tasks (Tavily, Exa, Valyu) are async — POST to start, GET to poll for results
  • Combine APIs: For thorough research, run Tavily + Exa + Linkup in parallel and cross-reference results

Discover More

List all endpoints for any API, or add a path for parameter details:

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":"tavily API endpoints"}' api show exa
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/search \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt":"andi API endpoints"}' api show linkup
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/search \
  -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt":"valyu API endpoints"}' api show searchapi

Example: curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/details \ -H "Authorization: Bearer $GOOSEWORKS_API_KEY" \ -H "Content-Type: application/json" \ -d '{"api":"tavily","path":"/search"}' for full parameter 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/web-search 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

Web Search 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.

Web Search compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Web Search this skillgooseworks-ai/goose-skills1.2k1 repos~4.2kAutomated safety check: PassMIT
Pi Web Searchsickn33/agentic-awesome-skills47k1 repos~925Automated safety check: PassMIT
Last30days Researchsandbaseai/sandbase-skills203—~676Automated safety check: PassApache-2.0
Agent ReachPanniantong/Agent-Reach95k—~1.4kAutomated safety check: PassMIT
Agent ReachEdisonChenAI/agent-reach1151 repos~1.3kAutomated safety check: PassMIT
YouTube Channel ToolsZeroPointRepo/youtube-skills1k1 repos~3.3kAutomated safety check: PassMIT

Similar skills

  • Pi Web Search

    sickn33/agentic-awesome-skills

    Give Pi Agents a safe web-search and fetch workflow using the installed pi-web-access package.

    47k GitHub starsUsed in 1 repo~925 tokens
    Productivity & AutomationAuto-check passed

  • Last30days Research

    sandbaseai/sandbase-skills

    Research any topic across the last 30 days using Reddit, Twitter, YouTube, Hacker News, web search, and news sources through SandBase.

    203 GitHub stars~676 tokensUpdated 15 days ago
    Productivity & AutomationAuto-check passed

  • Agent Reach

    Panniantong/Agent-Reach

    Routes web research and platform lookups across 16 sites, including Twitter, Reddit, YouTube, Bilibili, Xiaohongshu and GitHub, through one command-line tool.

    95k GitHub stars~1.4k tokensUpdated 3 days ago
    Productivity & AutomationAuto-check passed

  • Agent Reach

    EdisonChenAI/agent-reach

    Use the internet: search, read, and interact with 13+ platforms including Twitter/X, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu (小红书), Douyin (抖音), WeChat Articles (微信公众号), LinkedIn, Boss直聘…

    115 GitHub starsUsed in 1 repo~1.3k tokens
    Productivity & AutomationAuto-check passed

  • YouTube Channel Tools

    ZeroPointRepo/youtube-skills

    Browses YouTube channels through TranscriptAPI: resolves handles to channel IDs, lists recent uploads and pages through a channel's videos.

    1k GitHub starsUsed in 1 repo~3.3k tokens
    Productivity & AutomationAuto-check passed

  • Scrapingbee CLI

    ScrapingBee/scrapingbee-cli

    Fetch and read any web page, search the web, crawl a site, or pull structured data out of pages.

    108 GitHub stars~3.2k tokensUpdated 4 days ago
    Productivity & AutomationAuto-check: notes

More from gooseworks-ai/goose-skills

All 273 skills in this repo

  • Reddit Post Finder

    gooseworks-ai/goose-skills

    Scrape and search Reddit posts using Apify. An agent skill from gooseworks-ai/goose-skills.

    1.2k GitHub starsUsed in 1 repo~1.2k tokens
    Auto-check passed

  • Create Image Fal

    gooseworks-ai/goose-skills

    Generate or edit an image via any FAL image model (nano-banana edit, gpt-image, flux, ...), ROUTED THROUGH THE fal-proxy so it bills the Ads agent.

    1.2k GitHub stars~1.3k tokensUpdated yesterday
    Auto-check passed

  • Render Hook Replacement

    gooseworks-ai/goose-skills

    Replace an existing video's opening with a supplied clip or free kinetic text hook while retaining and verifying every original body frame, audio, captions and ending.

    1.2k GitHub stars~2.3k tokensUpdated yesterday
    Auto-check passed

  • Blog Feed Monitor

    gooseworks-ai/goose-skills

    Scrape blog posts via RSS feeds (free, no API key) with Apify fallback for JS-heavy sites.

    1.2k GitHub starsUsed in 1 repo~578 tokens
    Auto-check passed

  • Competitor Post Engagers

    gooseworks-ai/goose-skills

    Find leads by scraping engagers from a competitor's top LinkedIn posts.

    1.2k GitHub starsUsed in 1 repo~1.8k tokens
    Auto-check: notes

  • Render Chatgpt Chat

    gooseworks-ai/goose-skills

    Assemble a ChatGPT chat-reveal video ad from a thread + timeline JSON — one continuous Playwright recording of a ChatGPT mobile chat (user types with the iOS keyboard up → taps send → keyboard…

    1.2k GitHub stars~2.3k tokensUpdated yesterday
    Auto-check passed

Works with

Categories

Questions about Web Search

What does Web Search do?

Search the web, platforms, and datasets. An agent skill from gooseworks-ai/goose-skills. Web Search is an agent skill from gooseworks-ai/goose-skills. Search the web, platforms, and datasets.

When should I use Web Search?

Web Search fits situations like: asked to search; discover information from the web; academic sources; any online platform.

How do I install Web Search in Claude Code?

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

How do I install Web Search in Codex?

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

Can I use Web Search 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 web-search -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/web-search, .gemini/skills/web-search, .github/skills/web-search and .opencode/skills/web-search in your project.

What does Web Search need to run?

Going by SKILL.md and its folder, Web Search 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 Web Search 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 Web Search 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 Web Search use?

Web Search 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 Web Search use?

About 4.2k tokens (SKILL.md is roughly 17k 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 Web Search?

Skills that share tags, products or a category with Web Search: Pi Web Search (sickn33/agentic-awesome-skills, 47k stars), Last30days Research (sandbaseai/sandbase-skills, 203 stars), Agent Reach (Panniantong/Agent-Reach, 95k stars) and Agent Reach (EdisonChenAI/agent-reach, 115 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Web Search?

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.