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webshop-search-formulator

webshop-search-formulator

【设计与创意】This skill generates effective search keywords based on parsed product criteria. It is triggered after query parsing, when the agent needs to perform an initial product search on an e-commerce platform. The skill takes structured attributes (e.g., 'women's size 5 patent-beige high heel') and produces a concise, platform-appropriate search string desi…

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技能说明

GitHub

name: webshop-search-formulator description: This skill generates effective search keywords based on parsed product criteria. It is triggered after query parsing, when the agent needs to perform an initial product search on an e-commerce platform. The skill takes structured attributes (e.g., 'women's size 5 patent-beige high heel') and produces a concise, platform-appropriate search string designed to return relevant results, balancing specificity with recall.

Skill: Webshop Search Formulator

Purpose

You are an expert at formulating the initial search query for an e-commerce product search. Your goal is to translate a structured set of product requirements into a concise, effective search string that will yield relevant results on a platform like Amazon.

Core Workflow

  1. Input: You receive a parsed query containing key product attributes (e.g., category, type, size, color, material, price limit).
  2. Process: Analyze the attributes to identify the most critical, distinguishing features for the initial search. Prioritize attributes that will filter the results meaningfully without being overly restrictive.
  3. Output: Generate a single, well-formatted search[keywords] action string.

Key Principles for Search Formulation

  • Balance Specificity & Recall: Start with a moderately specific query. Including 2-3 core attributes (e.g., size 5 patent-beige high heel) is better than a single generic term (high heel) or an overly long list of all attributes.
  • Prioritize Distinctive Attributes: Favor attributes that uniquely identify the product variant (e.g., "patent-beige", "size 5") over very common ones (e.g., "women's") in the initial search.
  • Use Natural Keyword Order: Place the most important or specific terms first. Mimic how a user might type the query.
  • Exclude Non-Searchable Filters: Do not include filters typically applied after the search (e.g., price ranges like < $90) in the initial keyword string. These are for later refinement.
  • Standardize Formatting: Use lowercase, avoid special characters, and separate keywords with spaces.

Example from Trajectory

Parsed Instruction: woman's us size 5 high heel shoe with a rubber sole and color patent-beige, and price lower than 90.00 dollars Effective Search: search[size 5 patent-beige high heel] Rationale: "size 5" and "patent-beige" are the most specific, distinguishing attributes. "high heel" defines the product type. "rubber sole" and price filter are omitted from the initial search to avoid prematurely limiting potentially valid results.

Action Format

Your final output must be a single action in the exact format:

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