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Agent skill

Webshop Query Parser

by zjunlp in zjunlp/SkillNet

This skill extracts key constraints and product requirements from a user's shopping query.

MITAuto-check passedProduct & Project Management

Install Webshop Query Parser

skills CLI
$ npx skills add zjunlp/SkillNet --skill webshop-query-parser -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install zjunlp/SkillNet webshop-query-parser --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/zjunlp/SkillNet.git skills-src && mkdir -p .claude/skills && cp -r skills-src/experiments/src/skills/webshop/webshop-query-parser .claude/skills/webshop-query-parser && rm -rf skills-src

Use ~/.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/

Facts

Skill name
webshop-query-parser
GitHub stars
1.4k
Token cost
~663 tokens
SKILL.md length
311 words
Files
2 (incl. references)
Skills in repo
122
Repo updated
First seen
Licence
MIT

At a glance

This skill extracts key constraints and product requirements from a user's shopping query.

  • Works in 4 steps: Product Type/Name: The primary item the… → Key Attributes: Descriptive features… → Price Constraints: Any upper or lower… → …
  • Tasks that involve PRD writing
  • SKILL.md covers When to Use, Core Task, Procedure and Output, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Webshop Query Parser is an agent skill from zjunlp/SkillNet. 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.

Its SKILL.md is about 660 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/query_components.md`).

It sits in Product & Project Management, covering PRD writing. The repository describes itself as: Create, Evaluate, and Connect AI Skills. The licence is MIT.

When your agent uses it

  • Tasks that involve PRD writing

Example prompts

  • “gluten free”
  • “lower than 140.00 dollars”
  • “/webshop-query-parser”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  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.

What it can do on your machine

Read from SKILL.md and the folder at commit 358ec82. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Webshop Query Parser loads about 663 tokens when it runs, and up to ~1.2k if it reads all its reference files. Until then it costs about 102 tokens; SKILL.md has 311 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~102
When it runs · the whole SKILL.md, loaded when a task matches
~663
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.2k

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.

Safety

Auto-check passed

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from zjunlp/SkillNet at commit 358ec82, republished under its MIT licence (© zjunlp). 311 words, ~663 tokens.

Download SKILL.mdSave it as .claude/skills/webshop-query-parser/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
webshop-query-parser
description
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 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:

  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.

Procedure

  1. 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].

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.

© zjunlp, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in experiments/src/skills/webshop/webshop-query-parser of zjunlp/SkillNet.

  • SKILL.md
  • references/query_components.md

Open the folder on GitHubat commit 358ec82

Compare with similar skills

Webshop Query Parser 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.

Webshop Query Parser compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Webshop Query Parser this skillzjunlp/SkillNet1.4k—~663Automated safety check: PassMIT
CCPM Project Managementautomazeio/ccpm8.4k—~1.1kAutomated safety check: PassMIT
Ralph Tui Create Beadssubsy/ralph-tui2.5k1 repos~2.6kAutomated safety check: PassMIT
Trellis Brainstormanjiemo/SunnyBeach1787 repos~4kAutomated safety check: PassApache-2.0
Adversarial Speczscole/adversarial-spec5561 repos~8.3kAutomated safety check: NotesMIT
Ralph Tui Create Beads Rustsubsy/ralph-tui2.5k1 repos~2.8kAutomated safety check: PassMIT

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Categories

Questions about Webshop Query Parser

What does Webshop Query Parser do?

This skill extracts key constraints and product requirements from a user's shopping query. Webshop Query Parser is an agent skill from zjunlp/SkillNet. This skill extracts key constraints and product requirements from a user's shopping query.

When should I use Webshop Query Parser?

Webshop Query Parser fits situations like: tasks that involve PRD writing.

How do I install Webshop Query Parser in Claude Code?

Run `npx skills add zjunlp/SkillNet --skill webshop-query-parser -a claude-code`. Or copy the skill folder (experiments/src/skills/webshop/webshop-query-parser in zjunlp/SkillNet) into .claude/skills/webshop-query-parser in your project. Claude Code loads it when a task matches its description.

How do I install Webshop Query Parser in Codex?

Run `npx skills add zjunlp/SkillNet --skill webshop-query-parser -a codex`. Or copy the skill folder (experiments/src/skills/webshop/webshop-query-parser in zjunlp/SkillNet) into .agents/skills/webshop-query-parser in your project. Codex loads it when a task matches its description.

Can I use Webshop Query Parser in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add zjunlp/SkillNet --skill webshop-query-parser -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/webshop-query-parser, .gemini/skills/webshop-query-parser, .github/skills/webshop-query-parser and .opencode/skills/webshop-query-parser in your project.

What does Webshop Query Parser need to run?

SKILL.md names no scripts, command-line tools or credentials: Webshop Query Parser is instructions for the agent only.

Does Webshop Query Parser access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Webshop Query Parser safe to install?

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. Review the folder before installing.

What licence does Webshop Query Parser use?

Webshop Query Parser is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Webshop Query Parser use?

About 663 tokens (SKILL.md is roughly 2.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 555 tokens, read only when the agent opens those files.

What are the alternatives to Webshop Query Parser?

Skills that share tags, products or a category with Webshop Query Parser: CCPM Project Management (automazeio/ccpm, 8.4k stars), Ralph Tui Create Beads (subsy/ralph-tui, 2.5k stars), Trellis Brainstorm (anjiemo/SunnyBeach, 178 stars) and Adversarial Spec (zscole/adversarial-spec, 556 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Webshop Query Parser?

zjunlp (a GitHub organization) maintains it in zjunlp/SkillNet, which has 1,386 GitHub stars. The repository holds 122 skills in this directory. The repository was last updated on September 28, 2026.

Source: zjunlp/SkillNet on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.