SkillNet is infrastructure for finding, creating, evaluating, combining, and coordinating reusable capabilities for AI agents. Agent developers use it as a searchable and installable library of skills and as a system for selecting skills for particular tasks. The catalogue contains skills that can be discovered, installed, or used with SkillNet.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/zjunlp/skillnet/webshop-query-parsernpx skills add zjunlp/SkillNet --skill webshop-query-parsergit clone --depth 1 https://github.com/zjunlp/SkillNetWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/zjunlp/skillnet/webshop-query-parser)<a href="https://agentmods.dev/skills/zjunlp/skillnet/webshop-query-parser"><img src="https://agentmods.dev/badge/skills/zjunlp/skillnet/webshop-query-parser.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00079 | $0.00566 |
| Opus 5 | $0.00039 | $0.00283 |
| Sonnet 5 | $0.00016 | $0.00113 |
| Haiku 4.5 | $0.00008 | $0.00057 |
Grade A, and why
webshop-query-parser scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 33 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.pyon 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 besearch[gluten free popcorn].
- Example: For "i need gluten free popcorn, and price lower than 140.00 dollars", the script will output
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
clickactions 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.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 33 lines · 79 tokens per session scan A 83ad60b67e2a
webshop-query-parser is a skill published in the GitHub repository zjunlp/SkillNet (1,253 stars, last pushed yesterday), licensed MIT. It adds 79 tokens to every session and 566 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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