What makes pangolinfo-amazon-listing-optimization notable?

1.4K downloads. Trust evidence available

How should pangolinfo-amazon-listing-optimization be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

pangolinfo-amazon-listing-optimization

Use when: user says "写/优化 Listing" / "改我的标题" / "我的五点不行" / "Search Terms 怎么写" / "竞品文案怎么抄" / "rewrite my listing" / "我的转化率差" / "VOC 分析". Covers: 5-step Listing optimization — VOC 痛点挖掘 (来自 reviews) → 标题/五点/Backend 写作 → IP 合规自动筛查 → 文案可直接复制上架。 NOT for: 选品 (use amazon-product-explorer) / 日常监控 (use amazon- Skill: pangolinfo-amazon-listing-optimization Owner: pangolinfo Summary: Use when: user says "写/优化 Listing" / "改我的标题" / "我的五点不行" / "Search Terms 怎么写" / "竞品文案怎么抄" / "rewrite my listing" / "我的转化率差" / "VOC 分析". Covers: 5-step Listing optimization — VOC 痛点挖掘 (来自 reviews) → 标题/五点/Backend 写作 → IP 合规自动筛查 → 文案可直接复制上架。 NOT for: 选品 (use amazon-product-explorer) / 日常监控 (use amazon- Tags: latest:4.0.0 Version history: v4.0.0 | 2

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.4k

Updated

Oct 10, 2026

Version

4.0.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.4K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.4K downloadsadoption · observed Oct 10, 2026
Latest release: 4.0.0release · observed Aug 20, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s1713qcay2x7frr7y0mm908crx83hmg8:pangolinfo-amazon-listing-optimization

Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-pangolinfo-pangolinfo-amazon-listing-optimization/snapshot"

Documentation

CLAWHUB

148,453 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

SKILL.md

---
name: amazon-listing-optimization
description: |
  Use when: user says "写/优化 Listing" / "改我的标题" / "我的五点不行" / "Search Terms 怎么写" / "竞品文案怎么抄" / "rewrite my listing" / "我的转化率差" / "VOC 分析".
  Covers: 5-step Listing optimization — VOC 痛点挖掘 (来自 reviews) → 标题/五点/Backend 写作 → IP 合规自动筛查 → 文案可直接复制上架。
  NOT for: 选品 (use amazon-product-explorer) / 日常监控 (use amazon-daily-competitor-radar) / 单纯 ASIN 详情 (call get_amazon_product directly).
version: 3.1.0
mcp_tools_used:
  - pangolinfo_capabilities
  - search_amazon
  - get_amazon_product
  - get_amazon_reviews
  - ai_search
  - wipo_search
  - get_category_paths
  - search_amazon_alexa
applies_to: [claude-code, cursor, cline, windsurf, hermes, codex, openclaw]
budget:
  fast: { duration: "≤ 90s", cost: "≤ 10 积点", calls: "≤ 5" }
  full: { duration: "≤ 4min", cost: "≤ 40 积点", calls: "≤ 12" }
---

# Amazon Listing 优化 SOP

> 跑前必读：本文件末尾《核心规则 / Core Rules》章节（已内联，自包含）。
> **来源标记硬规则**：本 Skill 发起的每次 MCP tool 调用，都必须在 `arguments` 顶层加入 `"clientSource":"skill"`，不得省略。
> 角色：资深 Amazon 运营 + 文案专家。所有输出可直接复制到 Seller Central。

## 用户触发与档位

**Fast 档**（默认 ≤90s）：
- "帮我写个 Listing for wireless earbuds"
- "我的标题怎么改"
- "Backend Search Terms 怎么填"

**Full 档**（用户明示 ≤4min）：
- "完整重写 Listing 包括 A+ 文案"
- "深度 VOC 分析后再写"
- "包括 IP 合规筛查"

**单工具直通**：
- "查 X 的差评" → `get_amazon_reviews filterByStar=critical pageCount=1`
- "X 词在美国注册商标了吗" → `wipo_search source=USID hol=X`

---

## Fast 档 SOP(4 回合 ≤ 90s)

只用 PDP 自带的 `aiReviewsSummary` + 1 次 critical reviews,**不调** ai_search(30s 太慢)。

```
回合 1 (5s)   search_amazon                                          ← 找 Top 3 标杆 ASIN
回合 2 (5s)   get_amazon_product(A1) | get_amazon_product(A2)         ← 2 并发
回合 3 (5s)   get_amazon_product(A3) | get_amazon_reviews(最优 ASIN)  ← 2 并发(reviews 5pt)
回合 4 (5s)   get_category_paths (可选,验证类目锚定)                  ← 单发
LLM 整合 (~30s)
```

**总耗时**:~30s tool + 30s LLM ≈ **60-75s**
**总成本**:~8 积点(reviews 5pt + 3 个 PDP 各 1pt)
**总调用**:5-6 次 tool

**并发硬上限**: 2(实测 2026-05-28:3 并发会触发后端业务码 9200 "no content")。

### R1 — 找 Top 标杆 ASIN

```jsonc
{ "name": "search_amazon",
  "arguments": { "keyword": "<core_keyword>", "site": "amz_us" }}
```

**Extract**: `data.json[0].data.results[]` 取前 3 个非赞助（`sponsored="0"`）ASIN，按 `rank` 升序。

**Skip rule**: 用户已给了 3 个对标 ASIN → 跳过 R1。

### R2 — 2 并发拉标杆 PDP (A1 + A2)

```jsonc
{ "name": "get_amazon_product", "arguments": { "asin": "<A1>", "site": "amz_us" }}
{ "name": "get_amazon_product", "arguments": { "asin": "<A2>", "site": "amz_us" }}
```

**Data Ingestion Guard (any-field-empty)**: 对每个 ASIN,检查 4 个核心字段:
- `title` (string)
- `features` (array,至少 3 条)
- `aiReviewsSummary` (object)
- `bestSellersRankItems` (array,至少 1 条)

如果**全部**为 null → 输出 `🔴 Abort Maneuver: Target ASIN data body is completely empty.` 停止。
如果**任一**为 null(其他有数据) → 继续,但在 Section "Data Completeness Warnings" 里列出缺失字段 + 标明该分支用了 fallback。

**Extract per ASIN**:
- `title`:分析竞品标题结构
- `features[]`:竞品的"五点描述"(这是 features,不是不存在的 bullet_points)
- `productDescription[]`:A+ 模块(不是 a_plus_modules)
- `bestSell

_meta.json

{
  "ownerId": "kn78jnk9jg3dj6dqkcn0rdz4md83f361",
  "slug": "pangolinfo-amazon-listing-optimization",
  "version": "4.0.0",
  "publishedAt": 1787214612004
}

skill-card.md

## Description:

Helps Amazon sellers and operators optimize listings by using competitor product data, review-derived customer pain points, keyword placement, backend search terms, and IP compliance checks to produce copy-ready listing content.

This skill is ready for commercial/non-commercial use.

## Publisher:

[pangolinfo](https://clawhub.ai/user/pangolinfo)

### License/Terms of Use:

MIT-0

## Use Case:

External Amazon marketplace sellers and commerce operators use this skill to rewrite and optimize product listings, including titles, bullet points, backend search terms, and review-informed positioning. The skill is intended for workflows that combine Amazon product evidence with human review before publishing to Seller Central.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: A real Pangolinfo API key could be exposed if credentials are placed in URLs, logs, or model-visible transcripts.

Mitigation: Prefer MCP or runtime-managed authentication, keep credentials out of URLs and generated text, and review the skill before installing it in environments that contain a real Pangolinfo key.

## Reference(s):

- [ClawHub skill page](https://clawhub.ai/pangolinfo/skills/pangolinfo-amazon-listing-optimization)
- [Pangolinfo publisher profile](https://clawhub.ai/user/pangolinfo)

## Skill Output:

**Output Type(s):** [text, markdown, API calls, guidance]

**Output Format:** [Markdown listing analysis and copy drafts with structured sections]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Outputs may include Amazon listing titles, bullet points, backend search terms, VOC analysis, category notes, and IP compliance guidance for human review.]

## Skill Version(s):

4.0.0 (source: server release evidence)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

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