listinggood-amazon-suspension-shield

listinggood-amazon-suspension-shield is a skill for Claude Code, Codex from DedeGroup/listinggood-skills. It costs 183 tokens per session (1,793 once invoked), scanned A, original, MIT.

A guide for checking whether an Amazon seller account or listing could be suspended or taken down. It covers risks such as intellectual-property complaints, restricted categories, authenticity claims, linked accounts, unsafe products, and misleading or disallowed content.

In plain words
What is it for?
Use it to assess a listing before scaling sales, investigate a takedown or suspension, review brand and counterfeit risks, check restricted-product requirements, and examine EU compliance markings.
Why use it?
It looks beyond search keywords and listing quality at violations that can remove listings or accounts. It helps identify serious risks before they lead to warnings, complaints, or suspension.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to assess a listing before scaling sales, investigate a takedown or suspension, review brand and counterfeit risks, check restricted-product requirements, and examine EU compliance markings.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/dedegroup/listinggood-skills/listinggood-amazon-suspension-shield
Install

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.

Any agent
npx skills add DedeGroup/listinggood-skills --skill listinggood-amazon-suspension-shield
Clone the repo
git clone --depth 1 https://github.com/DedeGroup/listinggood-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for listinggood-amazon-suspension-shield

README.md
[![agentmods](https://agentmods.dev/badge/skills/dedegroup/listinggood-skills/listinggood-amazon-suspension-shield/github.svg)](https://agentmods.dev/skills/dedegroup/listinggood-skills/listinggood-amazon-suspension-shield)
Your own site
<a href="https://agentmods.dev/skills/dedegroup/listinggood-skills/listinggood-amazon-suspension-shield"><img src="https://agentmods.dev/badge/skills/dedegroup/listinggood-skills/listinggood-amazon-suspension-shield/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.

agentmods 80×15 button for listinggood-amazon-suspension-shield

Your own site · 80×15
<a href="https://agentmods.dev/skills/dedegroup/listinggood-skills/listinggood-amazon-suspension-shield"><img src="https://agentmods.dev/badge/skills/dedegroup/listinggood-skills/listinggood-amazon-suspension-shield.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 183 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,793 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00183 $0.01793
Opus 5 $0.00092 $0.00897
Sonnet 5 $0.00037 $0.00359
Haiku 4.5 $0.00018 $0.00179

Measured 12d ago against content hash 70c59aae2c66, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

listinggood-amazon-suspension-shield 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 12d 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.

skills/listinggood-amazon-suspension-shield/SKILL.md · 138 lines

How it starts

The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Amazon Suspension Shield — Account & Listing Takedown Risk Audit

Most "Amazon compliance" checkers only look at keyword coverage (title/bullets/SEO). That is the easy part. Sellers lose accounts and listings to suspension-risk violations — IP complaints, authenticity reports, linked-account bans, missing compliance markings. This skill audits that higher-stakes layer, the one that actually shuts businesses down.

Field notes below come from operating DeDe Fashion (HK fashion trade, 2016–present) and Alexis Leroy (live EU apparel/footwear brand on DE/ES/FR/IT). They are pattern knowledge, not legal advice.

When to Use

Trigger when the user asks about:

  • Why an account was suspended / a listing taken down
  • Whether a listing or account carries suspension risk before scaling ad spend
  • Brand / IP / counterfeit complaints
  • Category gating, restricted products, approval requirements
  • Linked-account (关联) ban risk
  • Review manipulation, Vine, solicited reviews
  • EU compliance markings (GPSR, 欧代/responsible person, CE, WEEE, textile label)
  • "My competitor reported me" / "I got a warning"

Workflow

Step 1: Gather Context

Field Required Notes
Listing text (title + bullets + A+ + description) The content to audit
Category / product type Drives which suspension rules apply
Marketplace(s) US vs EU vs JP enforcement differs sharply
Brand ownership status Own brand? Licensed? Reselling? Bundling?
Fulfillment Optional FBA vs FBM (affects some risk types)
Account age / prior warnings Optional Repeat violations escalate faster

Step 2: Run the Suspension-Risk Audit

Score each dimension. Severity drives the report.

2.1 Brand & Intellectual Property (highest account-level risk)
  • Competitor brand names in title/bullets/A+? (e.g., "compatible with Nike") → trademark complaint
  • Logo, pattern, or colorway that mimics a known brand?
  • Cartoon / movie / celebrity / sports-team IP without license?
  • Using "generic" but shipping branded units (authenticity mismatch)?
  • ⚠️ A single upheld IP complaint can trigger account-level review, not just takedown.

Read the full file on GitHub · 138 lines

Files

What ships with it

2 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.

Changes

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.

  1. 12d ago First seen · 138 lines · 183 tokens per session scan A 70c59aae2c66

Subscribe to this mod's changes

listinggood-amazon-suspension-shield is a skill published in the GitHub repository DedeGroup/listinggood-skills (1 stars, last pushed 7d ago), licensed MIT. It adds 183 tokens to every session and 1,793 once invoked, about $0.0009 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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