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 skills add xjli360/sealeap-amazon-ad-skills --skill sealeap-amazon-return-rate-reductiongit clone --depth 1 https://github.com/xjli360/sealeap-amazon-ad-skillsWrote 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/xjli360/sealeap-amazon-ad-skills/sealeap-amazon-return-rate-reduction)<a href="https://agentmods.dev/skills/xjli360/sealeap-amazon-ad-skills/sealeap-amazon-return-rate-reduction"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-amazon-return-rate-reduction/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/xjli360/sealeap-amazon-ad-skills/sealeap-amazon-return-rate-reduction"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-amazon-return-rate-reduction.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00081 | $0.01111 |
| Opus 5.5 | $0.00032 | $0.00444 |
| Sonnet 5.5 | $0.00016 | $0.00222 |
| Haiku 4.5 | $0.00008 | $0.00111 |
Grade A, and why
sealeap-amazon-return-rate-reduction 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 1mo 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.
What it actually says
Amazon 退货率降低
目标
把可避免退货按根因分流，在 Amazon 允许的支持入口中更快解决安装、使用和零配件问题。
适用任务
- 安装或使用困难导致退货。
- 大件商品因小配件损坏整单退回。
- 评估电话、视频、说明书或 AI 客服。
开始前要拿到
- 退货原因、退款、客户联系主题、差评主题和批次质量数据。
- 当前站点 Product Support、说明书、视频、电话或零配件功能资格。
- 客服语言、时区、隐私、录音、升级和人工接管要求。
缺失的数据要明确列为缺口，并把结论标成事实、估算或假设；不要补造数字。
不可妥协的边界
- 联系方式只放在 Amazon 明确允许的字段和场景，不绕过平台消息规则。
- 售后过程中不得索要好评、引导改评、评价门控或把客户沉淀成未授权私域名单。
- AI 客服必须遵守隐私、披露、录音和消费者保护要求，并保留人工升级。
- 当前 Amazon 官方政策、帮助页、账户资格和后台实际字段优先于本 Skill 中的经验框架；规则可能变化时先核验。
- 默认提供诊断或草案。写入前展示对象、旧值、新值、影响、停止线与回退，核对用户已有授权是否覆盖对象、动作与预算；范围已明确授权时继续执行并回读核验，只有未覆盖或扩大的范围才请求批准。
- 不输出原素材的创作者身份、账号、链接、视频编号或可反查线索；当前业务证据的官方来源、采集时间和口径仍需保留。
第三方 MCP 数据
只有在本任务确实需要外部市场、竞品、关键词或公开网页证据时，才读取 references/mcp-data-plan.md，并使用 scripts/mcp_research.py。
- 先动态执行 tools/list、search-tools 和 describe，依据实时 inputSchema 构造参数，不照搬历史工具名。
- 凭证只从环境变量读取，不放进命令参数、URL、Skill、结果文件或 Git。
- tools/call 可能计费。调用前展示 Provider、工具名、无密钥参数、预计成本与输出位置，核对已有授权覆盖后才加 --allow-cost；该标志不是费用上限。
- 第三方数据标为估算或代理证据，记录 Provider、工具、无密钥参数、查询时间和原始结果位置；失败一次后记录缺口，不反复消耗额度。
- 脱敏结果用 --output 写到 Skill 包之外的任务私有目录；不假设安装位置受仓库 .gitignore 保护，不把运行结果写入 Skill 包。
工作流
1. 量化退货根因
按 ASIN、变体、批次、原因、时间和成本建立 Pareto，先处理高频且可避免问题。
2. 修正商品承诺
让图片、尺寸、兼容性、安装难度和限制与实物一致，减少购买前误解。
3. 补足自助支持
在当前官方允许的位置提供清晰说明书、故障排查、安装或使用视频，并验证移动端可读性。
4. 设计零配件闭环
为适合商品建立配件库存、资格、验证、防欺诈和物流 SLA，比较补件与整单退货成本。
5. 配置客服
使用合规号码或平台入口，建立语言覆盖、响应时限、AI 到人工升级和敏感问题处理。
6. 验证成效
比较实施前后退货率、原因分布、解决率、响应时长、成本和客户满意度。
判断标准
- 功能资格和联系方式规则已核对当前官方文档。
- 支持不与评价请求或营销再触达绑定。
- 退货下降没有以拒绝合法退款为代价。
必须交付的结果
- 退货根因 Pareto。
- 内容、说明、视频和配件修复清单。
- 客服与 AI 升级 SOP。
- 实施前后评估方案。
结尾列出数据窗口、关键假设、证据缺口、风险和下一步；如包含待执行动作，单独放在“待批准变更”中。
What ships with it
3 files 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.
- 1mo ago First seen · 85 lines · 81 tokens per session scan A e8d1155eecac
sealeap-amazon-return-rate-reduction is a skill published in the GitHub repository xjli360/sealeap-amazon-ad-skills (86 stars, last pushed 1mo ago), licensed MIT. It adds 81 tokens to every session and 1,111 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-07.
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