Evaluate proxy provider trustworthiness by classifying evidence tiers and risk markers.
npx skills add https://github.com/cuipengfei/prompts --skill jichang
Please help me install this Agent Skill. Skill: jichang Source: https://github.com/cuipengfei/prompts/tree/main/plugins/jichang/skills/jichang Command: npx skills add https://github.com/cuipengfei/prompts --skill jichang
When users ask whether a jichang/airport/VPN/proxy subscription provider is trustworthy, they often face SEO/affiliate noise and unreliable one-time speed-test claims; this Skill helps you separate evidence quality from risk so you don’t accidentally treat advertising as proof.
Ask the AI to evaluate a specific jichang provider (name or login page URL) and output evidence tiers, risk markers, and a low-exposure testing checklist instead of a recommendation.
High-intent search queries and answers about installing and using this skill.
To evaluate VPN or proxy subscription provider trustworthiness, classify evidence sources into tiers such as official, long-term measurements, community feedback, and SEO/affiliate noise. This separates advertising from proof, preventing one-time speed tests from skewing your due diligence.
Evidence-tier classification for jichang due diligence categorizes provider information into official, long-term measurements, negative reviews, community feedback, and SEO/affiliate tiers. It defines what each tier can and cannot prove, explicitly separating reliable claims from ad pollution.
Perform low-exposure testing on proxy subscriptions by starting with trials, avoiding annual prepayments and large deposits. Record performance metrics over time to minimize financial risk while gathering reliable data instead of accepting unstable guarantees.
Ad pollution affects VPN provider risk assessment because SEO and affiliate marketing create unreliable noise. Evaluating ad pollution flags domain-relationship uncertainty and payment exposure, ensuring you do not accidentally treat advertising or one-time tests as proof of trustworthiness.
You cannot get a stable recommended ranking for proxy providers. Risk assessment enforces explicit risk labeling and loss-minimizing guidance without producing stable recommendations, and refuses to provide instructions for evasion or bypassing detection.
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