How do I install the Webshop Query Parser skill?

Run npx skillmds@latest add diegosouzapw/webshop-query-parser in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Webshop Query Parser safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Webshop Query Parser?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Webshop Query Parser free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Webshop Query Parser?

diegosouzapw (@diegosouzapw) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Webshop Query Parser by diegosouzapw

Name: Webshop Query Parser
Rating: 4.5 (4 reviews)
Author: diegosouzapw

Webshop Query Parser

This skill extracts key constraints and product requirements from a user's shopping query. It should be triggered when the agent receives a new shopping instruction, to identify product attributes (e.g., 'gluten free'), price limits (e.g., 'lower than 140.00 dollars'), and other specifications. The skill outputs a structured set of search criteria to guide subsequent product discovery.

diegosouzapw Updated Sep 8, 2026 54 repo stars

File contents

Instructions

When to Use

Activate this skill immediately when a new shopping instruction is received from the user, before any search or click actions are performed.

Core Task

Parse the user's natural language instruction to extract structured search criteria. Your goal is to identify:

Product Type/Name: The primary item the user wants (e.g., "popcorn").
Key Attributes: Descriptive features like "gluten free", "organic", "vegan", etc.
Price Constraints: Any upper or lower price limits (e.g., "lower than 140.00 dollars").
Other Specifications: Brand, size, quantity, or other qualifying terms.

Procedure

Run the Parser: Execute the bundled script parse_query.py on the user's instruction.
Review & Refine: Examine the script's output. If the instruction is complex or ambiguous, use your judgment to refine the criteria. For example, ensure price limits are correctly interpreted as numeric ranges.
Formulate Search Strategy: Use the extracted criteria to plan the initial web search. Combine the Product Type with the most critical Key Attributes to form effective initial search keywords.
- Example: For "i need gluten free popcorn, and price lower than 140.00 dollars", the script will output {'product': 'popcorn', 'attributes': ['gluten free'], 'price_max': 140.0}. Your initial search should be search[gluten free popcorn].

Output

After parsing, hold the structured criteria in memory. Use it to:

Guide the formulation of search[keywords] actions.
Evaluate product listings and details during click actions to check for constraint compliance (especially price).
Inform your reasoning in the Thought: part of your response.

Notes

Keep the initial search query concise but precise. Prioritize must-have attributes from the user's instruction.
The price filter is often not available as a direct web action; you must manually check prices in the search results and product details.
If the initial search yields no results, consider broadening the search by removing less critical attributes one at a time, but always respect hard constraints like "gluten free" if specified.

---name: webshop-query-parserdescription: This skill extracts key constraints and product requirements from a user's shopping query. It should be triggered when the agent receives a new shopping instruction, to identify product attributes (e.g., 'gluten free'), price limits (e.g., 'lower than 140.00 dollars'), and other specifications. The skill outputs a structured set of search criteria to guide subsequent product discovery.---# Instructions## When to UseActivate this skill immediately when a new shopping instruction is received from the user, before any search or click actions are performed.## Core TaskParse the user's natural language instruction to extract structured search criteria. Your goal is to identify:1. **Product Type/Name:** The primary item the user wants (e.g., "popcorn").2. **Key Attributes:** Descriptive features like "gluten free", "organic", "vegan", etc.3. **Price Constraints:** Any upper or lower price limits (e.g., "lower than 140.00 dollars").4. **Other Specifications:** Brand, size, quantity, or other qualifying terms.## Procedure1. **Run the Parser:** Execute the bundled script `parse_query.py` on the user's instruction.2. **Review & Refine:** Examine the script's output. If the instruction is complex or ambiguous, use your judgment to refine the criteria. For example, ensure price limits are correctly interpreted as numeric ranges.3. **Formulate Search Strategy:** Use the extracted criteria to plan the initial web search. Combine the **Product Type** with the most critical **Key Attributes** to form effective initial search keywords. * **Example:** For "i need gluten free popcorn, and price lower than 140.00 dollars", the script will output `{'product': 'popcorn', 'attributes': ['gluten free'], 'price_max': 140.0}`. Your initial search should be `search[gluten free popcorn]`.## OutputAfter parsing, hold the structured criteria in memory. Use it to:* Guide the formulation of `search[keywords]` actions.* Evaluate product listings and details during `click` actions to check for constraint compliance (especially price).* Inform your reasoning in the `Thought:` part of your response.## Notes* Keep the initial search query concise but precise. Prioritize must-have attributes from the user's instruction.* The price filter is often not available as a direct web action; you must manually check prices in the search results and product details.* If the initial search yields no results, consider broadening the search by removing less critical attributes one at a time, but always respect hard constraints like "gluten free" if specified.

Frequently asked questions