MBA Best Seller Product Data - Confirm & Copy Final Agent Code

Describe

Describe your task

Refine

Refine the plan

SubAgents

Review all agents

Deploy

Deploy your agent

Review Final Agent Copy

Expand

[
  {
    "taskID": 224,
    "semanticTitleOfTask": "Oracle-based Web Query to Identify Best-Selling T-Shirt URLs",
    "taskDescription": "Provides up to three relevant Amazon or Merch by Amazon URLs featuring best-selling t-shirts in the specified category and timeframe. These URLs spotlight top-selling listings with current reviews, ratings, and best-seller rankings.",
    "inputDescription": "Takes in 'VARIABLE1' and 'VARIABLE2' to search for up to three relevant Amazon URLs featuring best-selling t-shirts. 'VARIABLE1' is the category and 'VARIABLE2' is the timeframe. These URLs should reflect highly popular listings based on recent performance within the last 30 days.",
    "inputRequired": [
      "VARIABLE1",
      "VARIABLE2"
    ],
    "outputDescription": "Returns a short list of up to three valid Amazon.com or Merch by Amazon URLs that are most relevant for the chosen category and timeframe, ensuring they display best-seller information and customer ratings.",
    "outputName": "amazon_category_urls",
    "promptInstruction": "Find top-selling t-shirts on Amazon or Merch by Amazon in the 'VARIABLE1' category trending in the last 'VARIABLE2'. Provide up to 3 direct product URLs or category URLs. Focus on pages that: 1) Show BSR 2) Have reviews/ratings 3) Are from legitimate Amazon or Merch by Amazon sellers 4) Are relevant to the timeframe. Return only valid Amazon.com URLs with no extra text."
  },
  {
    "taskID": 225,
    "semanticTitleOfTask": "Amazon Page Crawl for T-Shirt Data",
    "taskDescription": "This task crawls each identified Amazon URL to extract structured data for t-shirt listings, including titles, bullet points, prices, review counts, ratings, and best-seller ranks. It consolidates the results for further processing.",
    "inputDescription": "Takes the list of Amazon URLs discovered in the previous task (#224). For each URL, it accesses the webpage, extracts product details, and compiles them into a structured dataset ready for filtering and validation.",
    "inputRequired": [
      "amazon_category_urls"
    ],
    "outputDescription": "Generates a comprehensive dataset containing all raw t-shirt listing data from each crawled page, capturing key information such as title, bullet points, price, reviews, rating, and BSR.",
    "outputName": "raw_tshirt_data",
    "promptInstruction": ""
  },
  {
    "taskID": 223,
    "semanticTitleOfTask": "Filter and Validate Final T-Shirt Listings",
    "taskDescription": "Removes listings with fewer than three reviews, checks for any potentially offensive or policy-violating content, and ensures each valid product has complete fields (title, bullet points, description, price, reviews, rating, BSR).",
    "inputDescription": "Takes the raw dataset of t-shirt listings from task (#225), a minimum reviews threshold, and Amazon content policy rules. Excludes any incomplete or disallowed listings based on the specified criteria, returning only valid entries.",
    "inputRequired": [
      "raw_tshirt_data",
      "minimum_reviews_threshold",
      "content_policy_rules"
    ],
    "outputDescription": "Produces a refined list of t-shirt listings that meet the minimum review count, adhere to content policy rules, and provide all critical product details. This final dataset is ready for ranking or further output.",
    "outputName": "filtered_product_listings",
    "promptInstruction": "Review this list of t-shirt data and remove any entries with fewer than 3 reviews or that appear to violate Amazon content guidelines. Ensure each remaining listing has a complete title, bullet points, description, price, reviews count, rating, and BSR if available. Return only valid entries as a structured array."
  },
  {
    "taskID": 2231,
    "semanticTitleOfTask": "Sort and Rank T-Shirt Listings Based on Multiple Criteria",
    "taskDescription": "This task sorts a list of t-shirt listings using multi-level priority (BSR, rating, review count, price) to produce a fully sorted array of listings.",
    "inputDescription": "Requires an array of filtered t-shirt listings containing BSR, price, review count, and rating fields, along with instructions specifying the sort order and priority.",
    "inputRequired": [
      "filtered_product_listings",
      "sorting_instructions"
    ],
    "outputDescription": "A sorted array of t-shirt listings in proper order, preserving the original fields of each listing.",
    "outputName": "sorted_listings_array",
    "promptInstruction": "You are a data sorting specialist. Your task is to sort the provided t-shirt listings according to these criteria in order of priority: 1) BSR (lowest first), 2) Average Rating (highest first), 3) Review Count (highest first), 4) Price (lowest first). If items tie, move to the next criterion. Return the entire array, preserving all fields and structure."
  },
  {
    "taskID": 2232,
    "semanticTitleOfTask": "Extract and Format Top 5 T-Shirt Listings",
    "taskDescription": "This task takes the sorted array of t-shirt listings, selects the top 5, and appends a numeric rank field from 1 to 5.",
    "inputDescription": "Requires a sorted array of t-shirt listings plus instructions specifying how many listings to extract, as well as how to assign rank fields.",
    "inputRequired": [
      "sorted_listings_array",
      "extraction_count",
      "rank_append_instructions"
    ],
    "outputDescription": "An array of exactly 5 t-shirt listings with the new 'rank' field for each listing, preserving all original fields and values.",
    "outputName": "top5_ranked_listings",
    "promptInstruction": "You are a data formatting specialist. From the sorted array, extract the top 5 listings, add a 'rank' field labeled 1 through 5, and return them in the same structure, preserving all fields. Ensure the output array contains exactly 5 items."
  },
  {
    "taskID": 311,
    "semanticTitleOfTask": "Data Preparation Phase - Gather Inputs",
    "taskDescription": "Collect the top_5_listings, category_name, date_analyzed, and JSON schema instructions from prior subagents, and aggregate them for JSON formatting.",
    "inputDescription": "Requires the outputs from previous steps, which include the array of top 5 t-shirt listings, the name of the category, the date analyzed, and the JSON schema instructions.",
    "inputRequired": [
      "top5_ranked_listings",
      "category_name",
      "date_analyzed",
      "json_schema_requirements"
    ],
    "outputDescription": "Outputs a combined data structure containing all necessary inputs required for the JSON construction phase.",
    "outputName": "prepared_data_for_json",
    "promptInstruction": ""
  },
  {
    "taskID": 312,
    "semanticTitleOfTask": "JSON Construction Phase - Use Skill #223",
    "taskDescription": "Use skill #223 to transform the aggregated t-shirt listings, category name, and date analyzed into a valid JSON string following the specified schema guidelines.",
    "inputDescription": "Receives the combined data from Task 311, including the top 5 listings, category name, date analyzed, and JSON schema instructions.",
    "inputRequired": [
      "prepared_data_for_json"
    ],
    "outputDescription": "A single well-formed JSON string containing the fields 'category', 'date_analyzed', and 'products' (with rank, title, bullet_points, description, price, reviews, and primary_keywords).",
    "outputName": "final_json_in_memory",
    "promptInstruction": "You are a JSON formatting specialist. Transform the provided product data into a valid JSON string that adheres to this schema: top-level keys 'category', 'date_analyzed', 'products'; exactly 5 product objects each with 'rank', 'title', 'bullet_points', 'description', 'price', 'reviews' (count, rating), and 'primary_keywords'. Return only the final JSON string with no additional commentary."
  },
  {
    "taskID": 313,
    "semanticTitleOfTask": "Output Delivery Phase - Return Final JSON",
    "taskDescription": "Return the finalized JSON string from memory as the subagent’s final output.",
    "inputDescription": "Requires the JSON string produced by Task 312.",
    "inputRequired": [
      "final_json_in_memory"
    ],
    "outputDescription": "The subagent's final output, containing the t-shirt data in the requested JSON format.",
    "outputName": "completed_json_output",
    "promptInstruction": ""
  },
  {
    "taskID": 185,
    "semanticTitleOfTask": "Write JSON Content to Final Output File",
    "taskDescription": "Takes the completed JSON string containing the top 5 t-shirt data and writes it exactly as provided to a new file named 'top5_tshirts.json', preserving all formatting and structure.",
    "inputDescription": "Two inputs are used: the final JSON string (which contains fully formatted t-shirt information) and a string specifying the output filename. Both are required to perform the file write operation accurately.",
    "inputRequired": [
      "final_json_in_memory",
      "output_filename"
    ],
    "outputDescription": "The result of this task is an output file named 'top5_tshirts.json' containing the t-shirt data in the requested JSON format, ensuring no modifications are made to the content.",
    "outputName": "top5_tshirts_json_file",
    "promptInstruction": ""
  },
  {
    "taskID": 223,
    "semanticTitleOfTask": "Analyze Top 5 Products for Keywords and Themes",
    "taskDescription": "Uses an LLM to parse the textual fields (titles, bullet points, descriptions) of 5 t-shirt listings, extracting recurring keywords and broader thematic elements while ignoring generic terms.",
    "inputDescription": "Requires a structured list of the top 5 products (including titles, bullet points, and descriptions), a list of generic terms to ignore, and any analysis parameters for keyword extraction and theme identification.",
    "inputRequired": [
      "top5_ranked_listings",
      "generic_terms_exclusion_list",
      "analysis_parameters"
    ],
    "outputDescription": "Generates a concise text summary identifying 3–5 recurring keywords (with frequency if repeated) and 2–3 overarching themes, capturing meaningful patterns across the listings.",
    "outputName": "recurring_keywords_themes_summary",
    "promptInstruction": "Examine the product titles, bullet points, and descriptions for the 5 t-shirt listings. Identify repeated words/phrases and main thematic elements, excluding generic t-shirt terms unless truly pertinent. Output a concise list of recurring keywords (with frequencies) and 2–3 key themes that appear across multiple designs."
  },
  {
    "taskID": 223001,
    "semanticTitleOfTask": "Validate T-Shirt Listing Data Structure",
    "taskDescription": "Analyzes incoming t-shirt listing data to ensure it contains all required fields (title, bullet_points, description, price, reviews), with correct data types and non-empty text fields.",
    "inputDescription": "Takes a JSON array of t-shirt data, each item requiring title, bullet_points (2 entries), description, price, review count, and rating. Also requires validation criteria to compare against.",
    "inputRequired": [
      "structured_listings",
      "validation_requirements"
    ],
    "outputDescription": "Returns 'VALID' if all data passes the checks, or a list of validation errors otherwise.",
    "outputName": "validated_listing_data",
    "promptInstruction": "You are a data structure validator for t-shirt listing analysis. Examine the provided t-shirt listing data and verify it contains all required fields: title, bullet_points (array of 2), description, price, and reviews (count, rating). Return 'VALID' if all checks pass, or list the validation errors found."
  },
  {
    "taskID": 223002,
    "semanticTitleOfTask": "Extract and Analyze Recurring Keywords from T-Shirt Listings",
    "taskDescription": "Processes validated t-shirt listing content to identify frequently occurring words, phrases, and thematic elements across all listings, counting frequencies and grouping related terms.",
    "inputDescription": "Requires validated listing data with titles, bullet points, and descriptions. Also takes any specific parameters for keyword analysis, enabling extraction of significant words/phrases and discovery of patterns.",
    "inputRequired": [
      "validated_listing_data",
      "analysis_parameters"
    ],
    "outputDescription": "Produces detailed keyword findings including frequency counts, contextual usage, and preliminary thematic groupings.",
    "outputName": "raw_keyword_analysis",
    "promptInstruction": "You are a keyword analysis specialist for t-shirt listings. Inspect the validated data’s titles, bullet points, and descriptions to extract meaningful words and phrases, count their frequencies, and note thematic or brand references. Ignore generic terms (e.g., 'size', 'cotton')."
  },
  {
    "taskID": 223003,
    "semanticTitleOfTask": "Refine and Rank Discovered Keywords/Themes",
    "taskDescription": "Combines similar terms and refines the raw keyword analysis, ranking by frequency, prominence in listing, and correlation with product performance, then categorizes them.",
    "inputDescription": "Takes raw keyword analysis and ranking criteria (e.g., frequency thresholds, rating considerations) to unify similar keywords and compute final significance scores.",
    "inputRequired": [
      "raw_keyword_analysis",
      "ranking_criteria"
    ],
    "outputDescription": "A refined list of keywords and themes, assigned significance scores (1–100), and grouped into main themes, design elements, audience indicators, and seasonal references.",
    "outputName": "refined_keyword_data",
    "promptInstruction": "You are a keyword optimization specialist. Consolidate similar terms, rank by frequency and placement prominence (title > description), consider reviews/ratings, and provide a significance score for each keyword or theme. Organize them by categories such as main themes or seasonal references."
  },
  {
    "taskID": 223004,
    "semanticTitleOfTask": "Generate Keyword Analysis Report",
    "taskDescription": "Creates a concise final report summarizing the refined keyword data, highlighting top keywords/themes, main findings, and marketing insights.",
    "inputDescription": "Requires the refined keyword data, which includes significance scores and thematic groupings, plus any required format specifications for producing the final text-based summary.",
    "inputRequired": [
      "refined_keyword_data",
      "report_format_requirements"
    ],
    "outputDescription": "A text report containing an executive summary, top keywords with frequency and significance, theme breakdown, and strategic marketing insights under 1000 characters length.",
    "outputName": "final_keyword_report",
    "promptInstruction": "You are a t-shirt market analysis report writer. From the refined keyword data, prepare a concise report containing an executive summary, top keywords with their significance, a theme analysis, and marketing insights. Format in clear sections with bullet points where appropriate."
  }
]

Happy? Now Copy-Paste To Proceed...

BACK TO SUBAGENTS

COPY TO CLIPBOARD