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-attribute-verifiernpx skills add zjunlp/SkillNet --skill webshop-attribute-verifiergit 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-attribute-verifier)<a href="https://agentmods.dev/skills/zjunlp/skillnet/webshop-attribute-verifier"><img src="https://agentmods.dev/badge/skills/zjunlp/skillnet/webshop-attribute-verifier.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 | $0.00119 | $0.00788 |
| Opus 5 | $0.00060 | $0.00394 |
| Sonnet 5 | $0.00024 | $0.00158 |
| Haiku 4.5 | $0.00012 | $0.00079 |
Grade A, and why
webshop-attribute-verifier 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instructions
You are verifying product attributes on a detailed product page. Your goal is to confirm the product matches the user's requirements before proceeding.
Input
You receive an Observation containing:
- The original user instruction (e.g., "find a black leather wallet, price lower than 40.00 dollars")
- Product details: Title, Price, Rating
- Available options (e.g., color buttons like "black", "brown")
- Available actions (e.g., "Buy Now", "Back to Search", "Description")
Core Workflow
- Parse Requirements: Extract every target attribute from the user instruction — color, material, size, max price, and any other constraints.
- Inspect Page: Read the observation for the product's displayed price, title, available option buttons, and specifications.
- Compare Price: Confirm the product's price is strictly lower than the user's maximum price. If not, navigate back immediately.
- Verify Attributes: Check each remaining requirement (color, material, size, etc.) against the product's details and available options.
- Select or Reject:
- If all requirements are satisfied,
click[option]on the required attribute (e.g.,click[black]) first, thenclick[Buy Now]. - If any requirement fails,
click[Back to Search]to find a different product.
- If all requirements are satisfied,
Action Format
click[value]— interact with a page element. Thevaluemust exactly match a clickable item from the observation.search[keywords]— start a new search only if the current product cannot meet requirements.- Every response must begin with
Thought:stating which requirement is being checked and the verdict.
Critical Rules
- Price is strict: The price must be strictly less than the user's budget — equal is not acceptable.
- Select before buying: Always click the required attribute option (e.g.,
click[black]) before clickingclick[Buy Now]. Never skip this step. - One action per turn: Output exactly one action after your
Thought:.
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 · 72 lines · 119 tokens per session scan A 511ece6aa6d3
webshop-attribute-verifier is a skill published in the GitHub repository zjunlp/SkillNet (1,253 stars, last pushed yesterday), licensed MIT. It adds 119 tokens to every session and 788 once invoked, about $0.0006 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.
Other skills, from other repositories
skill-creator
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
ddr-globem-analysis
Analyze a specific participant's longitudinal passive-sensing and psychological data in the GLOBEM digital depression research dataset. Use this skill whenever the task involves: analyzing a user's mental health or behavioral data from wearables/smartphones, generating QA pairs about behavioral/psychological changes…
applicable-fee-ids
Solve questions about which fee IDs apply to a payment merchant, transaction characteristics, or time period in the dabstep dataset. Use this skill for any question asking "which fee IDs apply to X", "what are the applicable fee IDs for merchant Y", "which merchants are affected by fee Z", or any query involving…
Fee_Delta_and_Impact_Simulation
Solve dabstep FeeDeltaandImpactSimulation questions: computing fee deltas when a fee's rate changes, and identifying which merchants are affected by fee rule changes. Use when asked about fee impact, delta payments, rate changes, or which merchants would be affected by modifying a fee rule.
Total_Fees_Calculation
Skill for computing total payment processing fees for a merchant over a specific day, date range, or month in the dabstep dataset. Use this skill whenever the question asks for "total fees", "fees paid", or "fees charged" for a merchant over some time period. The computation requires matching each transaction to a fee…
mimic-iv-patient-analysis
Comprehensive strategy for analyzing individual patient records in MIMIC-IV EHR database and generating high-quality, diverse QA pairs. Use this skill whenever the task involves analyzing a specific patient's clinical data from MIMIC-IV (or similar EHR databases), querying across hospital and ICU tables, and…