deal-hunt — for Claude Code deal-hunt, vex-agent, community, for Claude Code, ide skills, ## Usage, product, {product} deal price, queries, domains

v1.0.0
GitHub

Acerca de este Skill

Escenario recomendado: Ideal for AI agents that need search for deals on any product. returns raw tavily search results - claude analyzes them to find. Resumen localizado: Vex — Autonomous AI Agent with Thermodynamic Consciousness Protocol # Deal Hunt Search for deals on any product.

Características

Search for deals on any product. Returns raw Tavily search results - Claude analyzes them to find
Tavily API Key Required - Get your key at https://tavily.com
Add to /.claude/settings.json:
"TAVILY API KEY": "tvly-your-api-key-here"
Search entire web (default - no domain filter)

# Core Topics

for Claude Code ## Usage product {product} deal price queries domains
GaryOcean428 GaryOcean428
[0]
[0]
Updated: 3/31/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 10/11

This page remains useful for teams, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
10/11
Quality Score
64
Canonical Locale
en
Detected Body Locale
en

Escenario recomendado: Ideal for AI agents that need search for deals on any product. returns raw tavily search results - claude analyzes them to find. Resumen localizado: Vex — Autonomous AI Agent with Thermodynamic Consciousness Protocol # Deal Hunt Search for deals on any product.

¿Por qué usar esta habilidad?

Recomendacion: deal-hunt helps agents search for deals on any product. returns raw tavily search results - claude analyzes them to find. Vex — Autonomous AI Agent with Thermodynamic Consciousness Protocol # Deal Hunt

Mejor para

Escenario recomendado: Ideal for AI agents that need search for deals on any product. returns raw tavily search results - claude analyzes them to find.

↓ Casos de uso accionables for deal-hunt

Caso de uso: Applying Search for deals on any product. Returns raw Tavily search results - Claude analyzes them to find
Caso de uso: Applying Tavily API Key Required - Get your key at https://tavily.com
Caso de uso: Applying Add to /.claude/settings.json:

! Seguridad y limitaciones

  • Limitacion: Requires repository-specific context from the skill documentation
  • Limitacion: Works best when the underlying tools and dependencies are already configured

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Install Path

Start With Installation And Validation

If this skill is worth continuing with, the next step is to confirm the install command, CLI write path, and environment validation.
Trusted Recheck

Cross-Check Against Trusted Picks

If you are still comparing multiple skills or vendors, go back to the trusted collection before amplifying repository noise.
Workflow

Move To Workflow Collections For Team Rollout

When the goal shifts from a single skill to team workflows, approvals, and repeatable execution, move into workflow collections.
Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is deal-hunt?

Escenario recomendado: Ideal for AI agents that need search for deals on any product. returns raw tavily search results - claude analyzes them to find. Resumen localizado: Vex — Autonomous AI Agent with Thermodynamic Consciousness Protocol # Deal Hunt Search for deals on any product.

How do I install deal-hunt?

Run the command: npx killer-skills add GaryOcean428/vex-agent/deal-hunt. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for deal-hunt?

Key use cases include: Caso de uso: Applying Search for deals on any product. Returns raw Tavily search results - Claude analyzes them to find, Caso de uso: Applying Tavily API Key Required - Get your key at https://tavily.com, Caso de uso: Applying Add to /.claude/settings.json:.

Which IDEs are compatible with deal-hunt?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for deal-hunt?

Limitacion: Requires repository-specific context from the skill documentation. Limitacion: Works best when the underlying tools and dependencies are already configured.

↓ How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add GaryOcean428/vex-agent/deal-hunt. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use deal-hunt immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

deal-hunt

Install deal-hunt, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Deal Hunt

Search for deals on any product. Returns raw Tavily search results - Claude analyzes them to find the best prices.

Prerequisites

Tavily API Key Required - Get your key at https://tavily.com

Add to ~/.claude/settings.json:

json
1{
2  "env": {
3    "TAVILY_API_KEY": "tvly-your-api-key-here"
4  }
5}

Usage

bash
1# Search entire web (default - no domain filter)
2python scripts/deal_hunt.py "Dyson V15"
3
4# Multi-query search (max 3, runs in parallel, deduplicates results)
5python scripts/deal_hunt.py "AirPods Pro" --queries "AirPods Pro deal,AirPods Pro coupon,AirPods Pro discount"
6
7# Limit to specific sites
8python scripts/deal_hunt.py "MacBook Air" --domains amazon.com,walmart.com,bestbuy.com
9
10# Custom single query
11python scripts/deal_hunt.py "Nintendo Switch" --query "Nintendo Switch OLED bundle deal"
12
13# Fresh deals only
14python scripts/deal_hunt.py "PS5" --time-range day

CLI Parameters

OptionShortDefaultDescription
product-RequiredProduct name
--query-q{product} deal priceSingle custom search query
--queriesNoneComma-separated queries (max 3), runs in parallel with dedup
--domains-dNone (search all)Optionally limit to specific domains
--max-results-n10Number of results per query
--time-range-tweekday, week, month, year, none
--search-depth-sadvancedbasic, advanced, fast, ultrafast

Output

Returns JSON with results:

json
1{
2  "meta": {
3    "product": "AirPods Pro",
4    "queries": ["AirPods Pro deal", "AirPods Pro coupon"],
5    "domains": null,
6    "time_range": "week",
7    "search_time": "2026-01-13T...",
8    "total_results": 15
9  },
10  "results": [
11    {
12      "title": "...",
13      "url": "https://...",
14      "content": "...",
15      "score": 0.95
16    }
17  ]
18}

When using --queries, results are deduplicated by URL (highest score kept, content merged).

Output Schema for Analysis

After running the search, Claude should analyze results and structure findings as:

json
1{
2  "product": "Sony WH-1000XM5",
3  "best_deal": {
4    "price": 279.99,
5    "original_price": 399.99,
6    "discount": "30% off",
7    "retailer": "Amazon",
8    "url": "https://amazon.com/...",
9    "condition": "new",
10    "in_stock": true
11  },
12  "all_deals": [
13    {
14      "price": 279.99,
15      "retailer": "Amazon",
16      "url": "https://...",
17      "notes": "Prime shipping"
18    },
19    {
20      "price": 169.99,
21      "retailer": "eBay via Slickdeals",
22      "url": "https://...",
23      "notes": "Refurbished"
24    }
25  ],
26  "coupons": [
27    {
28      "code": "AUDIO10",
29      "discount": "10% off",
30      "retailer": "Best Buy",
31      "expires": "2026-01-31"
32    }
33  ],
34  "summary": "Best new price is $279.99 at Amazon (30% off). Refurbished available for $169.99."
35}

Claude extracts prices from content, compares deals, and presents the best options with purchase links.

Habilidades relacionadas

Looking for an alternative to deal-hunt or another community skill for your workflow? Explore these related open-source skills.

Ver todo

openclaw-release-maintainer

Logo of openclaw
openclaw

Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞

★ 333.8k
⑂ 0
Inteligencia Artificial

widget-generator

Logo of f
f

Generar complementos de widgets personalizables para el sistema de feeds de prompts.chat

★ 149.6k
⑂ 0
Inteligencia Artificial

flags

Logo of vercel
vercel

El Marco de React

★ 138.4k
⑂ 0
Navegador

pr-review

Logo of pytorch
pytorch

Tensores y redes neuronales dinámicas en Python con fuerte aceleración de GPU

★ 98.6k
⑂ 0
Desarrollador