Product Reel Generator
gooseworks-ai/goose-skills
Generates Instagram-ready product reels from any e-commerce product page URL.
Walmart keyword search scraper: input a search keyword and page number, navigate to walmart.com search results, extract paginated product listings with itemId, url, title, brand, image, price…
$ npx skills add browser-act/skills --skill walmart-keyword-search -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install browser-act/skills walmart-keyword-search --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/browser-act/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/solutions/ecommerce/walmart-keyword-search .claude/skills/walmart-keyword-search && 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 "walmart-keyword-search" agent skill from https://github.com/browser-act/skills/tree/main/solutions/ecommerce/walmart-keyword-search into .claude/skills/walmart-keyword-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "walmart-keyword-search", 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/browser-act/skills/tree/main/solutions/ecommerce/walmart-keyword-searchType 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 browser-act/skills --skill walmart-keyword-search -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install browser-act/skills walmart-keyword-search --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/browser-act/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/solutions/ecommerce/walmart-keyword-search .agents/skills/walmart-keyword-search && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "walmart-keyword-search" agent skill from https://github.com/browser-act/skills/tree/main/solutions/ecommerce/walmart-keyword-search into .agents/skills/walmart-keyword-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "walmart-keyword-search", 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 browser-act/skills --skill walmart-keyword-search -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install browser-act/skills walmart-keyword-search --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/browser-act/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/solutions/ecommerce/walmart-keyword-search .cursor/skills/walmart-keyword-search && 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 "walmart-keyword-search" agent skill from https://github.com/browser-act/skills/tree/main/solutions/ecommerce/walmart-keyword-search into .cursor/skills/walmart-keyword-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "walmart-keyword-search", 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/browser-act/skills.git --path solutions/ecommerce/walmart-keyword-search--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 browser-act/skills --skill walmart-keyword-search -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install browser-act/skills walmart-keyword-search --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/browser-act/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/solutions/ecommerce/walmart-keyword-search .gemini/skills/walmart-keyword-search && 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 "walmart-keyword-search" agent skill from https://github.com/browser-act/skills/tree/main/solutions/ecommerce/walmart-keyword-search into .gemini/skills/walmart-keyword-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "walmart-keyword-search", 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 browser-act/skills walmart-keyword-searchInstalls 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 browser-act/skills --skill walmart-keyword-search -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/browser-act/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/solutions/ecommerce/walmart-keyword-search .github/skills/walmart-keyword-search && 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 "walmart-keyword-search" agent skill from https://github.com/browser-act/skills/tree/main/solutions/ecommerce/walmart-keyword-search into .github/skills/walmart-keyword-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "walmart-keyword-search", 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 browser-act/skills --skill walmart-keyword-search -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install browser-act/skills walmart-keyword-search --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/browser-act/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/solutions/ecommerce/walmart-keyword-search .opencode/skills/walmart-keyword-search && 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 "walmart-keyword-search" agent skill from https://github.com/browser-act/skills/tree/main/solutions/ecommerce/walmart-keyword-search into .opencode/skills/walmart-keyword-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "walmart-keyword-search", 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.
walmart-keyword-searchWalmart keyword search scraper: input a search keyword and page number, navigate to walmart.com search results, extract paginated product listings with itemId, url, title, brand, image, price…
Walmart Keyword Search is an agent skill from browser-act/skills. Walmart keyword search scraper: input a search keyword and page number, navigate to walmart.com search results, extract paginated product listings with itemId, url, title, brand, image, price, wasPrice, rating, reviewCount, availability, seller info, fulfillmentBadge, classType, and shortDescription. Use when user mentions walmart search, walmart keyword search, search walmart products, scrape walmart search results, walmart search scraper, walmart product search, search items on walmart, walmart search by…
Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/extract-listing.py`).
It sits in Sales & Support, covering E-commerce operations and Web scraping. It works with Python. The repository describes itself as: Browser automation CLI built for AI agents. Break through anti-bot walls, hand off to humans across platforms when stuck. Parallel multi-task execution, independent multi-session… The licence is MIT.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 11c057b. It shows what the files ask for, not the result of running them.
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.
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
pythonFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
walmart.comi5.walmartimages.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Walmart Keyword Search loads about 1.8k tokens when it runs. Until then it costs about 234 tokens; SKILL.md has 667 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.
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); the scripts in this folder are not scanned.
The full file from browser-act/skills at commit 11c057b, republished under its MIT licence (© browser-act). 667 words, ~1,777 tokens.
.claude/skills/walmart-keyword-search/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.keyword + page → paginated product list from walmart.com search results
All process output to user (progress updates, process notifications) follows the user's language.
Extract product listings from Walmart's keyword search results page, returning structured item data with pricing, rating, availability, and seller info.
https://www.walmart.com/search?q={keyword}&page={page}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.
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. Its role is equivalent to copy-pasting on the user's behalf — the data is already on screen, automation merely saves time. JS code is encapsulated in Python files under the
scripts/directory, invoked viaeval "$(python scripts/xxx.py {params})".$(...)is bash syntax; it is recommended to use the bash tool for execution.
Below are all atomic capabilities discovered and verified during the exploration phase, listed by command template with parameters. Simply invoke them as needed — no need to read scripts/*.py source code or re-verify. Only inspect scripts when execution fails for troubleshooting. Combine freely as needed during execution.
Navigate to the target search URL first, then extract:
navigate "https://www.walmart.com/search?q={keyword}&page={page}&sort={sort}"wait stableeval "$(python scripts/extract-listing.py)"Parameters in URL:
{keyword}: URL-encoded search keyword (e.g., laptop, apple+iphone, running+shoes){page}: page number, starting from 1{sort}: sort order — best_match (default), price_low, price_high, rating_high, newOutput example:
{
"pageType": "SearchPage",
"query": "laptop",
"currentPage": 1,
"totalCount": 16174,
"maxPage": 12,
"itemCount": 57,
"items": [
{
"itemId": "18656507313",
"url": "https://www.walmart.com/ip/HP-14-N150-4-128-Blue/18656507313",
"title": "HP 14 inch HD Windows Laptop Intel Processor N150 4GB 128GB UFS Waterfall Blue",
"brand": null,
"image": "https://i5.walmartimages.com/seo/HP-14.jpeg",
"price": 229,
"priceString": "$229.00",
"wasPrice": null,
"rating": 4.2,
"reviewCount": 274,
"availability": "IN_STOCK",
"availabilityText": "In stock",
"sellerName": "Walmart.com",
"sellerType": null,
"fulfillmentBadge": null,
"classType": "VARIANT",
"shortDescription": null
}
]
}Error response (when extraction fails or wrong page):
{"error": true, "message": "No searchResult in __NEXT_DATA__. Ensure the page is fully loaded at the correct search URL."}sort [collection failed]: URL parameter values observed during exploration: best_match, price_low, price_high, rating_high, new. Full enum list not exposed via API or DOM; additional values may exist.
URL Pagination: URL pattern https://www.walmart.com/search?q={keyword}&page={N}&sort={sort}. Increment page by 1 each iteration. Termination: page > maxPage (from response maxPage field) OR itemCount === 0. Note: Walmart caps search results at maxPage (typically 11–25 pages max regardless of totalCount).
itemCount >= 1 AND items[0].itemId is non-null AND items[0].url starts with https://www.walmart.com/ip/
brand field is null for many items in search listing (available in product detail)shortDescription is null for most non-food items in search listingwasPrice is null unless the item has an active markdown/rollbacksellerType is null for Walmart.com first-party listingsPath: {working-directory}/browser-act-skill-forge-memories/walmart-scraper-walmart-keyword-search.memory.md (working directory is determined by the Agent running the Skill, typically the project root or current working directory)
Before execution: If the file exists, read it first — it records unexpected situations encountered during past executions (e.g., a strategy has become ineffective); adjust strategy order accordingly.
After execution: If an unexpected situation is encountered (strategy became ineffective, page redesigned, anti-scraping upgraded, better path discovered), append a line:
{YYYY-MM-DD}: {what happened} → {conclusion}
Normal execution does not write to the file. Do not record what keywords were used or how many results were returned — those are task outputs, not experience.
© browser-act, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (scripts) in solutions/ecommerce/walmart-keyword-search of browser-act/skills.
Open the folder on GitHubat commit 11c057b
Walmart Keyword 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Walmart Keyword Search this skillbrowser-act/skills | 6.1k | — | ~1.8k | Automated safety check: Pass | MIT | |
| Product Reel Generatorgooseworks-ai/goose-skills | 1.2k | 1 repos | ~2.3k | Automated safety check: Notes | MIT | |
| Etsy Shop Sales Historysickn33/agentic-awesome-skills | 47k | 1 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Extractactionbook/actionbook | 1.6k | 2 repos | ~3.4k | Automated safety check: Pass | Apache-2.0 | |
| Agentkeychainbase-labs/Agentkey | 656 | — | ~2.3k | Automated safety check: Pass | MIT | |
| Apify Ecommercesickn33/agentic-awesome-skills | 47k | 2 repos | ~2.3k | Automated safety check: Notes | MIT |
gooseworks-ai/goose-skills
Generates Instagram-ready product reels from any e-commerce product page URL.
sickn33/agentic-awesome-skills
Read Etsy shop sales counters, deltas, and breakout flags from Apify Actor publicrecords/etsy-shop-velocity (MCP panel snapshot).
actionbook/actionbook
Extract structured data from websites and produce an executable Playwright script plus extracted data.
chainbase-labs/Agentkey
PROACTIVELY use whenever the user needs data outside your training set or requires a live network call — web search, URL scraping, news, social media (any platform), market prices…
sickn33/agentic-awesome-skills
Extract product data, prices, reviews, and seller information from any e-commerce platform using Apify's E-commerce Scraping Tool.
apify/awesome-skills
Scrape e-commerce data for pricing, reviews, bestsellers, and seller discovery across 30+ platforms including Amazon, Walmart, eBay, Shopify, WooCommerce, and more.
browser-act/skills
Fetches structured Amazon product details such as title, price, ratings and availability for a given ASIN through BrowserAct's lookup API template.
browser-act/skills
Extracts structured Amazon product data for a keyword and marketplace through the BrowserAct API, including titles, prices, ratings, reviews, sales volume and promotions.
browser-act/skills
Pulls Amazon product details, competing seller prices and seller ratings for a given ASIN through the BrowserAct API, without browser automation.
browser-act/skills
Analyzes a competitor's Amazon listing by ASIN with BrowserAct data extraction, then reports what it does well, where the market has gaps and opportunity points for your own listing.
browser-act/skills
Pulls structured Amazon search results (titles, ASINs, prices, ratings, specifications) for a keyword and brand through BrowserAct's Amazon Product API template.
browser-act/skills
Collects structured product data from Amazon search results for a keyword and optional brand, using a BrowserAct script, for market and competitor research.
Works with
Categories
Walmart keyword search scraper: input a search keyword and page number, navigate to walmart.com search results, extract paginated product listings with itemId, url, title, brand, image, price…. Walmart Keyword Search is an agent skill from browser-act/skills.com search results, extract paginated product listings with itemId, url, title, brand, image, price, wasPrice, rating, reviewCount, availability, seller info, fulfillmentBadge, classType, and shortDescription.
Walmart Keyword Search fits situations like: user mentions walmart search; walmart keyword search; search walmart products; scrape walmart search results.
Run `npx skills add browser-act/skills --skill walmart-keyword-search -a claude-code`. Or copy the skill folder (solutions/ecommerce/walmart-keyword-search in browser-act/skills) into .claude/skills/walmart-keyword-search in your project. Claude Code loads it when a task matches its description.
Run `npx skills add browser-act/skills --skill walmart-keyword-search -a codex`. Or copy the skill folder (solutions/ecommerce/walmart-keyword-search in browser-act/skills) into .agents/skills/walmart-keyword-search in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add browser-act/skills --skill walmart-keyword-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/walmart-keyword-search, .gemini/skills/walmart-keyword-search, .github/skills/walmart-keyword-search and .opencode/skills/walmart-keyword-search in your project.
Going by SKILL.md and its folder, Walmart Keyword Search needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
SKILL.md names 2 domains. In commands or code: walmart.com and i5.walmartimages.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.
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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Walmart Keyword Search is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Walmart Keyword Search: Product Reel Generator (gooseworks-ai/goose-skills, 1.2k stars), Etsy Shop Sales History (sickn33/agentic-awesome-skills, 47k stars), Extract (actionbook/actionbook, 1.6k stars) and Agentkey (chainbase-labs/Agentkey, 656 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
browser-act (a GitHub organization) maintains it in browser-act/skills, which has 6,126 GitHub stars. The repository holds 87 skills in this directory. The repository was last updated on August 24, 2026.
Source: browser-act/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.