reddit-competitor-analysis-api-skill
This skill extracts structured data from Reddit posts and comments using the BrowserAct API, enabling users to analyze competitor mentions, track brand sentiment, conduct market research, and monitor community feedback. Use it when you need to search Reddit by keywords, filter posts by date range, sort results by relevance or engagement metrics, and compile nested comments for deep analysis without encountering CAPTCHAs or IP restrictions.
git clone --depth 1 https://github.com/browser-act/skills /tmp/reddit-competitor-analysis-api-skill && cp -r /tmp/reddit-competitor-analysis-api-skill/solutions/social-listening/reddit-competitor-analysis-api-skill ~/.claude/skills/reddit-competitor-analysis-api-skillSKILL.md
# Reddit Competitor Analysis API Skill ## 📖 Introduction This skill uses the BrowserAct Reddit Competitor Analysis API template to provide users with a one-stop Reddit data collection service. It can extract full post details and comments from Reddit search results. Just input search keywords and filtering conditions to directly get clean and usable Reddit data. ## ✨ Features 1. **No hallucinations, ensuring stable and precise data extraction**: Pre-set workflows avoid AI generative hallucinations. 2. **No CAPTCHA issues**: No need to handle reCAPTCHA or other verification challenges. 3. **No IP access restrictions or geofencing**: No need to handle regional IP limitations. 4. **Faster execution**: Compared to pure AI-driven browser automation solutions, task execution is faster. 5. **Extremely high cost-effectiveness**: Significantly reduces data acquisition costs compared to highly token-consuming AI solutions. ## 🔑 API Key Guide Before running, you must check the `BROWSERACT_API_KEY` environment variable. If it is not set, do not take any other actions; you should request and wait for the user to provide it collaboratively. **The Agent must inform the user at this time**: > "Since you have not configured the BrowserAct API Key, please go to the [BrowserAct Console](https://www.browseract.com/reception/integrations) to get your Key first." ## 🛠️ Input Parameters When calling the script, the Agent should flexibly configure the following parameters based on user needs: 1. **Keywords (Search keywords)** - **Type**: `string` - **Description**: Search keywords for Reddit posts. - **Example**: `openclaw` 2. **Publication_date (Publication date)** - **Type**: `string` - **Description**: Filter posts by publication date range. - **Options**: `All time`, `Past year`, `Past month`, `Past week`, `Today`, `Past hour` - **Default**: `Past week` 3. **Post_sort_by (Search sort)** - **Type**: `string` - **Description**: Sort Reddit post search results by selected criteria. - **Options**: `Relevance`, `Hot`, `Top`, `New`, `Comment count` - **Default**: `Relevance` 4. **Comment_sort_by (Comment sort)** - **Type**: `string` - **Description**: Sort extracted comments by. - **Options**: `Best`, `Top`, `New`, `Controversial`, `Q&A` - **Default**: `Best` 5. **Data_limit (Comments per post)** - **Type**: `number` - **Description**: Maximum number of comments to extract per post. - **Default**: `10` ## 🚀 Usage (Recommended) The Agent should execute the following independent script to achieve "one-line command to get results". Note that the script path `./scripts/...` is relative to this skill's directory: ```bash # Example invocation python3 -u ./scripts/reddit_competitor_analysis_api.py "keywords" "publication_date" "post_sort_by" "comment_sort_by" data_limit ``` ### ⏳ Task Status Monitoring Since this task involves automated browser operations, it may take a long time (several minutes). The script will **continuously output status logs with timestamps** (e.g., `[14:30:05] Task Status: running`) while running. **Agent Must Know**: - While waiting for the script to return results, please keep an eye on the terminal output. - As long as the terminal is still outputting new status logs, it means the task is running normally. Please do not mistakenly judge it as a deadlock or unresponsiveness. - Only if the status remains unchanged for a long time or the script stops outputting and no result is returned, you can consider triggering the retry mechanism. ## 🔧 OpenClaw Adaptation Guide Since BrowserAct tasks may take a long time to run (5-20 minutes), when the Agent executes in the OpenClaw environment, it needs to: 1. **Run in background mode (using JSON parameters for `exec` tool):** - `command`: `"python3 -u ./scripts/reddit_competitor_analysis_api.py ..."` - `background`: `true` - `timeout`: `1800` 2. **Or increase yieldMs:** - `command`: `"python3 -u ./scripts/reddit_competitor_analysis_api.py ..."` - `yieldMs`: `600000` - `timeout`: `1800` 3. **Use process poll to monitor:** - `action`: `"poll"` - `sessionId`: `"xxx"` - `timeout`: `300000` ## 📊 Data Output Description After successful execution, the script will directly parse and print the results from the API response. The results include: - `post_title`: Full post title - `publish_time`: Post publication time - `like_count`: Number of upvotes on the post - `comment_count`: Total number of comments - `publish_channel`: Subreddit where the post was published - `comment_author`: Username of the commenter - `comment_time_utc`: Comment timestamp - `comments`: Full comment text - `comment_upvotes`: Number of upvotes on the comment - `comment_level`: Nesting level of the comment - `comment_author_url`: Link to the commenter's profile - `reply_to`: Parent comment or post being replied to ## ⚠️ Error Handling & Retry During the execution of the script, if an error occurs (such as network fluctuation or task failure), the Agent should follow this logic: 1. **Check the output content**: - If the output **contains** `"Invalid authorization"`, it means the API Key is invalid or expired. At this time, **do not retry**, but guide the user to recheck and provide the correct API Key. - If the output **does not contain** `"Invalid authorization"` but the task execution fails (for example, the output starts with `Error:` or the returned result is empty), the Agent should **automatically try to execute the script again**. 2. **Retry limit**: - Automatic retry is limited to **one time**. If the second attempt still fails, stop retrying and report the specific error message to the user.
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Extracts Airbnb accommodation search results from a destination query via SSR-embedded data, returning listing ID, URL, name, coordinates, rating, price, photos, and badge info for each result, plus pagination cursors for multi-page retrieval. Use when user mentions Airbnb search results, Airbnb listings, vacation rental search, short-term rental listings, scrape Airbnb, get Airbnb data, find rentals on Airbnb, Airbnb destination search, Airbnb property list, Airbnb stays search, Airbnb accommodation results, pull Airbnb listings, collect Airbnb search data, Airbnb scraper, Airbnb search page extraction, Airbnb search by destination.
Amazon Alexa for Shopping Q&A automation: submits questions to Amazon's Alexa/Rufus AI shopping assistant and collects response text; supports optional keyword search context (navigate to search results page before asking for category-specific answers). Use when user mentions Amazon Alexa, Rufus, Amazon shopping assistant, Amazon AI chat, ask Amazon, Amazon Q&A, automate Alexa questions, Rufus chatbot, Amazon assistant automation, collect Alexa responses, bulk question submission to Amazon, keyword search context, category research. Also applies to extracting Amazon product recommendations from conversational AI, automating repeated queries to Amazon's AI shopping feature, collecting Alexa shopping responses at scale, or market research within a specific product category.
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This skill helps users extract structured best-selling product data from Amazon via the BrowserAct API. Agent should proactively apply this skill when users express needs like search for best selling products on Amazon, extract Amazon product data based on keywords, find top rated Amazon products, monitor Amazon competitor prices and sales, discover trending products on Amazon marketplace, extract Amazon product titles prices and ratings, gather Amazon product sales volume for market research, search Amazon best sellers in specific region, collect Amazon product reviews and promotion details, analyze Amazon product availability and badges, get Amazon product data for market analysis.
Amazon Best Sellers listing scraper: extract product cards from any Amazon Best Sellers (zgbs) or /gp/bestsellers/ category page — returns rank (position on chart), asin, title, url, image, imageAlt, price, stars, reviewCount, ratingRaw per item, plus category metadata (categoryName, categoryFullName, categoryUrl) and pagination state (currentPage, hasNextPage, nextPageUrl). Works across all Amazon regional TLDs (amazon.com, amazon.co.uk, amazon.de, amazon.co.jp, amazon.fr, amazon.it, amazon.es, amazon.ca, amazon.com.au, amazon.in, etc.). Use when user mentions Amazon Best Sellers, Amazon bestsellers, Amazon top 100, Amazon zgbs, Amazon /zgbs/, Amazon /gp/bestsellers/, Amazon Best Sellers Rank, Amazon BSR, Amazon top ranked products, Amazon top-selling products, Amazon chart, Amazon category ranking, Amazon best sellers by category, Amazon best sellers electronics, Amazon best sellers kitchen, Amazon best sellers toys, scrape Amazon bestsellers, extract Amazon top 100, Amazon rank scraper, Amazon best seller list, Amazon leaderboard, Amazon trending products, discover trending Amazon products, Amazon niche discovery, Amazon top ranked ASINs. Also applies to competitive intelligence via ranking snapshots, spotting up-and-coming products, sourcing bestseller ASINs for further enrichment, tracking rank changes over time, and building bestseller-per-category datasets.
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