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-xiezhi-amazon-seasonal-portfolio-calendargit 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-xiezhi-amazon-seasonal-portfolio-calendar)<a href="https://agentmods.dev/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-seasonal-portfolio-calendar"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-seasonal-portfolio-calendar/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-xiezhi-amazon-seasonal-portfolio-calendar"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-seasonal-portfolio-calendar.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 | $0.00053 | $0.01148 |
| Opus 5.5 | $0.00021 | $0.00459 |
| Sonnet 5.5 | $0.00011 | $0.00230 |
| Haiku 4.5 | $0.00005 | $0.00115 |
Grade A, and why
sealeap-xiezhi-amazon-seasonal-portfolio-calendar 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 季节活动产品组合日历
目标
把每月不同的节日与社会活动需求编排成滚动产品组合，并以提前布局和保守库存控制季末风险。
适用任务
- 制定全年节日/活动选品日历。
- 复盘多 SKU 店铺的月度主力产品。
- 规划旺季前调研、上架、广告和补货节点。
开始前要拿到
- 目标站点的全年活动与文化日历。
- 至少两年的商品、关键词和销量季节曲线。
- 研发、采购、生产、运输和入仓时效。
- SKU 级库存、利润和季末清货约束。
缺少字段时列出证据缺口，并把相关结论标为 FACT、ESTIMATE、ASSUMPTION 或 UNKNOWN；不要补造数据。
不可妥协的边界
- 第三方数据均为估算或代理证据；Amazon 一方报告、后台实时字段和产品事实优先。
- 经验阈值只能作为可调起点，必须展示敏感性分析，不能写成 Amazon 官方规则。
- 不得捏造销量、搜索量、CPC、CVR、成本、认证、产品属性或消费者需求。
- 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。
- 不输出或保存素材来源身份、账号、链接、作品编号、互动数据、原始话术或其他可反查来源的线索。
- 不得使用未经许可的节日 IP、宗教表达或文化符号。
- 不得以违规评价或变体操作保留历史权重。
工作流
1. 建立日历
按月列出全国节日、地方活动、学校周期、婚礼派对和职业感谢等场景，并标注文化适配风险。
2. 寻找需求载体
为每个场景匹配批量采购、礼赠、装饰、收纳或活动耗材等产品形态。
3. 复盘历史
查看往年起量、峰值、回落、价格和低评论样本，区分稳定周期与一次性事件。
4. 倒排执行
通常在峰值前三至五个月启动调研，并确保峰值前有足够上架与学习时间；实际节点由交期计算。
5. 保守备货
以可比低评论正常样本、目标份额和清货周期制定首批量，设置缺货容忍与季末退出方案。
6. 滚动复盘
每月更新预测与库存，把第一年的真实结果转化为下一年的供应、素材和广告基线。
判断标准
- 提前三至五个月是规划启发式，不适用于所有供应链。
- 节日产品的低老链接权重可能给新品窗口，但不能视为公平流量保证。
- 宁可错失部分峰值也不能用无证据预测压入不可清退库存。
第三方 MCP 数据
需要外部关键词、竞品、评论或公开网页证据时，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。 - 凭证只从环境变量读取，不进入参数、URL、Skill、终端输出或 Git。
- 可能计费的
tools/call先展示 Provider、工具、无密钥参数、预计成本与输出位置，核对已有授权；仅在授权覆盖本次范围时使用--allow-cost，该标志不是费用上限。 - 脱敏结果用
--output写入 Skill 包之外的任务私有目录；不假设安装位置受仓库.gitignore保护。第三方数据标为估算或代理证据。 - 失败一次后记录缺口，不以重复付费重试掩盖不可用状态。
必须交付的结果
- 年度机会日历
- SKU 上市倒排甘特
- 历史季节证据表
- 首批备货与退出规则
- 月度复盘模板
结尾列出站点、数据窗口、证据来源、关键假设、缺口、风险、下一步和所有待批准动作。证据不足时写 HOLD，不得包装成可直接执行。
执行细节、证据字段和质量检查见 references/playbook.md。
What ships with it
4 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 · 90 lines · 53 tokens per session scan A 2fb21aadae16
sealeap-xiezhi-amazon-seasonal-portfolio-calendar is a skill published in the GitHub repository xjli360/sealeap-amazon-ad-skills (86 stars, last pushed 1mo ago), licensed MIT. It adds 53 tokens to every session and 1,148 once invoked, about $0.0002 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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