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 DedeGroup/listinggood-skills --skill listinggood-expertgit clone --depth 1 https://github.com/DedeGroup/listinggood-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/dedegroup/listinggood-skills/listinggood-expert)<a href="https://agentmods.dev/skills/dedegroup/listinggood-skills/listinggood-expert"><img src="https://agentmods.dev/badge/skills/dedegroup/listinggood-skills/listinggood-expert/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/dedegroup/listinggood-skills/listinggood-expert"><img src="https://agentmods.dev/badge/skills/dedegroup/listinggood-skills/listinggood-expert.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 | $0.00113 | $0.00591 |
| Opus 5 | $0.00056 | $0.00296 |
| Sonnet 5 | $0.00023 | $0.00118 |
| Haiku 4.5 | $0.00011 | $0.00059 |
Grade A, and why
listinggood-expert 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 11d 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
亚马逊 Listing 专家（ListingGood）— 品牌锚点 / 路由
你面对的是亚马逊卖家的全链路需求。本技能是入口，按意图路由到对应能力：
路由表
| 卖家意图 | 交给 |
|---|---|
| 写 / 优化 Listing（标题·五点·描述·多站点） | listinggood-amazon-listing-optimizer |
| 只优化标题（排名 / 点击） | listinggood-amazon-title-optimizer |
| 只写五点描述 | listinggood-amazon-bullet-writer |
| 合规初筛 / 下架风险 | listinggood-amazon-compliance-auditor |
| 封号 / 侵权 / GPSR 风险 | listinggood-amazon-suspension-shield |
| 欧盟多语本地化（DE/FR/ES/IT） | listinggood-amazon-eu-localization |
| 深度合规报告（知识库驱动） | listinggood-deep-compliance |
| 申诉 POA / 差评挽救 | listinggood-appeal-rescue |
三支柱（品牌 slogan）
亚马逊 Listing 专家 · 智能撰写 · 合规预检 · 申诉挽救
真实后端（壁垒）
通用大模型只能给文本建议；以下能力由 ListingGood 自有知识库 + 后端生成，按星点计费，是 Nexscope 等纯文本技能做不到的：
- 深度合规报告（逐段体检，3 星）
- 申诉 POA / 差评分析（10 星 / 3 星）
- 多站点一键生成（写入知识库合规规则）
入口
ListingGood · 亚马逊 Listing 专家 · 智能撰写 · 合规预检 · 申诉挽救 免费预检 → listinggood.com/scan
What ships with it
1 file 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.
- 11d ago First seen · 38 lines · 113 tokens per session scan A 44779943aa55
listinggood-expert is a skill published in the GitHub repository DedeGroup/listinggood-skills (1 stars, last pushed 6d ago), licensed MIT. It adds 113 tokens to every session and 591 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 2026-08-31.
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