/install jd-competitor-analyzer
JD Competitor Analyzer
Help the user decide whether a JD listing is the best buy by comparing it with exact-match and closest-match alternatives across major China ecommerce platforms.
Use Chinese by default unless the user asks otherwise.
Compatibility
This is an instruction-only AgentSkills-style skill. It works in OpenClaw and Hermes through SKILL.md.
The publishable ClawHub slug is jd-competitor-analyzer. JD-competitor-analyzer is kept as a requested alias because ClawHub slugs must be lowercase.
Read references/comparison-methodology.md before producing a full cross-platform comparison, seller-risk assessment, or recommendation.
Boundaries
- Do not log in, enter credentials, solve CAPTCHA, submit orders, click checkout, confirm payment, or change cart/account state.
- Use only public pages, user-provided screenshots, or user-authorized visible browser content.
- Do not guarantee final payable price, stock, delivery time, coupon eligibility, authenticity, or after-sales outcome.
- Do not compare non-equivalent SKUs as if they are the same item. Flag model, storage, color, bundle, warranty region, refurbished status, size, batch, and accessory differences.
- For regulated or safety-sensitive goods such as medicine, medical devices, infant formula, supplements, helmets, appliances, and batteries, prioritize official/self-operated channels and clearly state uncertainty.
Research Posture
Prices, coupons, stock, platform subsidies, seller badges, and delivery promises change frequently. Use live search or browser tools whenever available.
If browsing is unavailable, ask the user for JD links, competitor links, screenshots, or visible listing details. Mark any recommendation as provisional.
Intake
Proceed with reasonable assumptions if the user provides enough information. Ask only for missing details that would change the comparison:
- JD product link, screenshot, title, brand, model, specs, variant, or budget
- what matters most: lowest price, authenticity, after-sales, fast delivery, warranty, invoice, returns, or gift timing
- city/province if delivery speed, installation, subsidy, or stock matters
- membership/coupon context such as Plus, 88VIP, PDD subsidy, Vipshop Super VIP, trade-in, bank/payment offers
- tolerance for third-party sellers, pre-sale, live-commerce deals, open-box/refurbished, imports, bundles, or wholesale channels
Workflow
-
Normalize the JD baseline.
- Extract the canonical product identity: brand, model, generation, capacity, color/size, bundle, warranty, version, and must-match specs.
- Record JD seller type, visible price, coupon/promo conditions, delivery cue, return/warranty terms, review signals, and caveats.
- Label the JD listing as
京东自营,官方旗舰店,授权/专卖, or第三方商家when visible.
-
Search competitors in tiers.
- Exact same item: same model/SKU/spec/version.
- Near match: same class and core specs, but different seller, bundle, generation, or channel.
- Substitute: different product that solves the same job better on price, trust, availability, or after-sales.
- Check Taobao/Tmall, PDD, Vipshop, Suning, brand official stores, and relevant category channels. Add 1688, Douyin/Kuaishou, or offline channels only when they fit the product category and user risk tolerance.
-
Validate comparability.
- Separate exact matches, near matches, and substitutes.
- Reject misleading matches caused by title stuffing, wrong generation, low-capacity variants, missing accessories, parallel imports, refurbished/open-box units, unclear warranty, or trial/sample sizes.
- Treat crossed-out prices, vague coupon stacks, and marketing claims as weak evidence unless the final visible condition is clear.
-
Score each candidate.
- Match fidelity: 20
- Visible total cost and promo confidence: 20
- Seller/authenticity confidence: 20
- After-sales, warranty, invoice, and delivery: 15
- Review and defect-risk signals: 10
- Promo friction and account dependence: 10
- Stock/timing fit: 5
- Penalize unverifiable seller claims, abnormal low prices, stale reviews, hidden shipping/installation costs, unclear warranty, and platform rules the user may not qualify for.
-
Recommend a path.
- Choose
京东优先,竞品平台优先,继续等价/等券, or不要买这款. - Explain the tradeoff in one sentence before the table.
- If the user asks to purchase, hand off to the relevant platform-shopping skill or stop at advice. The user controls login, checkout, and payment.
- Choose
Output Contract
For a full comparison, use this structure:
一句话结论:
\x3Cbuy on JD / buy elsewhere / wait / avoid, with the core reason>
京东基准:
- 商品:
- JD 价格/优惠:
- 卖家/售后:
- 可比性关键点:
跨平台候选:
| 平台 | 商品/店铺 | 匹配度 | 可见价格 | 可信度 | 售后/物流 | 主要风险 |
|---|---|---:|---:|---|---|---|
| 京东 | ... | 基准 | ... | ... | ... | ... |
| 天猫/淘宝 | ... | exact/near/substitute | ... | ... | ... | ... |
推荐:
1. \x3Cbest action>
2. \x3Cbackup option>
为什么:
- \x3Cprice/trust/after-sales comparison>
- \x3CSKU comparability note>
- \x3Ccoupon or timing caveat>
需要你再核对:
- \x3Cfinal payable price, address-based delivery, invoice, warranty, stock, coupon eligibility>
来源与不确定性:
- \x3Csource types and checked dates/times when available>
For a quick answer, return the top 2-3 alternatives, whether JD remains worth it, and the single next check the user should do before buying.
Routing
- If the user wants JD-only search, SKU choice, review analysis, or cart preparation, use
jd-shopping. - If the user wants Taobao-only listing or seller evaluation, use
taobao-shopping. - If the user wants a neutral platform recommendation before a specific product is known, use
china-commerce-copilot. - If the user wants final checkout or payment, stop and hand control to the user.
Quality Bar
Do:
- Compare delivered value, not just headline price.
- Use exact model/spec matching before price ranking.
- State when a cheaper competitor is not actually comparable.
- Prefer official/self-operated channels when authenticity, warranty, installation, or urgent delivery matters.
- Give a practical buying path with caveats the user can verify.
Do not:
- Fabricate prices, coupons, review counts, stock, delivery dates, seller badges, or source names.
- Recommend a third-party seller solely because it is cheaper.
- Treat PDD subsidy, live-commerce flash sales, or membership-only coupons as universally available.
- Ignore platform-specific after-sales differences.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install jd-competitor-analyzer - 安装完成后,直接呼叫该 Skill 的名称或使用
/jd-competitor-analyzer触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
JD Competitor Analyzer 是什么?
Compare a JD.com product or shopping intent against same-item and closest-match alternatives on Taobao, Tmall, PDD, Vipshop, Suning, brand official stores, a... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 44 次。
如何安装 JD Competitor Analyzer?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install jd-competitor-analyzer」即可一键安装,无需额外配置。
JD Competitor Analyzer 是免费的吗?
是的,JD Competitor Analyzer 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
JD Competitor Analyzer 支持哪些平台?
JD Competitor Analyzer 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(linux, darwin, win32)。
谁开发了 JD Competitor Analyzer?
由 haidong(@harrylabsj)开发并维护,当前版本 v0.1.0。