Agent skill

Sealeap Baize Amazon Conversion Root Cause

by xjli360 in xjli360/sealeap-amazon-skills

Diagnose weak Amazon conversion product-first by benchmarking comparable listings, market difficulty, price-value fit, visual differentiation, keyword precision, and placement mix.

MITAuto-check passedDevelopment

Install Sealeap Baize Amazon Conversion Root Cause

skills CLI
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-baize-amazon-conversion-root-cause -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install xjli360/sealeap-amazon-skills sealeap-baize-amazon-conversion-root-cause --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/amazon-skills/douyin/baize/sealeap-baize-amazon-conversion-root-cause .claude/skills/sealeap-baize-amazon-conversion-root-cause && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
sealeap-baize-amazon-conversion-root-cause
GitHub stars
247
Token cost
~537 tokens
SKILL.md length
117 words
Files
5 (incl. scripts, references)
Skills in repo
179
Repo updated
First seen
Licence
MIT

At a glance

Diagnose weak Amazon conversion product-first by benchmarking comparable listings, market difficulty, price-value fit, visual differentiation, keyword precision, and placement mix.

  • Works in 4 steps: 诊断:读取现状、证据和缺口,不生成线上写入动作。 → 方案草案:输出可审核的结构、参数范围、实验和回退值。 → 执行准备:只生成待批准变更表或 API/控制台操作草案。 → …
  • 产品转化差、广告不出单、价格还是图片问题、词不准还是商品页问题、商品页位置差
  • SKILL.md covers 目标, 不可妥协的边界, 先判断任务模式 and 开始前要拿到, plus 3 more sections
  • Runs Python scripts from its folder

What it does

Sealeap Baize Amazon Conversion Root Cause is an agent skill from xjli360/sealeap-amazon-skills. Diagnose weak Amazon conversion product-first by benchmarking comparable listings, market difficulty, price-value fit, visual differentiation, keyword precision, and placement mix. Use for 产品转化差、广告不出单、价格还是图片问题、词不准还是商品页问题、商品页位置差.

Its SKILL.md is about 540 tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/mcp-data-plan.md` and `references/playbook.md`).

It sits in Development, covering Root cause analysis. It works with Model Context Protocol. The repository describes itself as: Reusable Agent Skills for Amazon product research, listings, advertising, inventory, and operations. The licence is MIT.

When your agent uses it

  • 产品转化差、广告不出单、价格还是图片问题、词不准还是商品页问题、商品页位置差
  • Tasks that involve Root cause analysis

Example prompts

  • “/sealeap-baize-amazon-conversion-root-cause”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. 诊断:读取现状、证据和缺口,不生成线上写入动作。
  2. 方案草案:输出可审核的结构、参数范围、实验和回退值。
  3. 执行准备:只生成待批准变更表或 API/控制台操作草案。
  4. 已批准执行:仅对用户在当前会话明确批准的对象和字段执行,并立即回读核验。

What it can do on your machine

Read from SKILL.md and the folder at commit 497d4b8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Sealeap Baize Amazon Conversion Root Cause loads about 537 tokens when it runs, and up to ~2.6k if it reads all its reference files. Until then it costs about 68 tokens; SKILL.md has 117 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~68
When it runs · the whole SKILL.md, loaded when a task matches
~537
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from xjli360/sealeap-amazon-skills at commit 497d4b8, republished under its MIT licence (© xjli360). 117 words, ~537 tokens.

Download SKILL.mdSave it as .claude/skills/sealeap-baize-amazon-conversion-root-cause/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
sealeap-baize-amazon-conversion-root-cause
description
Diagnose weak Amazon conversion product-first by benchmarking comparable listings, market difficulty, price-value fit, visual differentiation, keyword precision, and placement mix. Use for 产品转化差、广告不出单、价格还是图片问题、词不准还是商品页问题、商品页位置差.

Amazon 商品转化根因排查

目标

Diagnose weak Amazon conversion product-first by benchmarking comparable listings, market difficulty, price-value fit, visual differentiation, keyword precision, and placement mix.

不可妥协的边界

  • 当前 Amazon 官方政策、账户资格、站点字段和一方数据优先于本 Skill 的经验框架。
  • 第三方数据一律标为估算或前台观测,不得写成 Amazon 一方事实。
  • 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。
  • 一次实验只改变一个主要变量,并记录基线、样本、成功、停止和回退条件。
  • 不得复制来源材料或竞品表达;输出必须按当前任务重新组织并可由现有证据支撑。
  • 先产品后广告是诊断顺序,不代表广告永远不是根因。
  • 所有竞品和销量比较都需保留来源、站点、时间与限制。

先判断任务模式

  1. 诊断:读取现状、证据和缺口,不生成线上写入动作。
  2. 方案草案:输出可审核的结构、参数范围、实验和回退值。
  3. 执行准备:只生成待批准变更表或 API/控制台操作草案。
  4. 已批准执行:仅对用户在当前会话明确批准的对象和字段执行,并立即回读核验。

用户未指定时采用“诊断”。

开始前要拿到

  • marketplace、ASIN/SKU、产品事实和当前 Listing
  • 同购买意图可比竞品、价格、评论、图片和销量
  • Search Term、Placement、CTR、CVR、订单、退货和利润
  • VOC、Q&A、退货原因与任何页面或广告变更日志

缺失项必须标为 NEEDS_EVIDENCE;不得猜数字、补属性或把不同站点、ASIN、变体、币种和时间窗混在一起。

工作流

先读取 references/playbook.md,确认该方法适用于当前对象。按以下顺序执行:

  1. 先建立同站点、同意图、外观价格和评论基础接近的可比组。
  2. 比较本品与可比组销量,再判断所在成熟度层的市场难度。
  3. 核对价格差是否有明确价值证据承接。
  4. 评估主图在缩略图中是否传达真实差异,而非只看美观。
  5. 产品侧无明显缺口后,再查广告词相关性、位置和搜索词。

最后做数据充分性检查,并把结论分成 FACT / ESTIMATE / HYPOTHESIS / UNKNOWN。若关键证据不足,状态写 HOLD。

第三方 MCP 数据

仅在自有数据不足且当前任务确实需要外部证据时,读取 references/mcp-data-plan.md,再使用 scripts/mcp_research.py。本 Skill 的外部取数目的:获取可比竞品、评论层级、价格、关键词和自然可见度代理数据。

  • 先 doctor,再 search-tools 和 describe;工具名及参数以实时 tools/list 与 inputSchema 为准。
  • Token 只从环境变量读取。不得写入命令参数、URL、Skill、报告、日志或 Git。
  • tools/call 或 Actor 可能计费;先展示 Provider、工具、无密钥业务参数、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。

必须交付的结果

  • 产品侧四层诊断
  • 广告侧复核
  • 首要根因
  • 单变量改进实验
  • 数据范围、来源、采集时间、样本与限制。
  • 关键假设、待补证据、风险和不可确定项。
  • 若有动作:对象、旧值、新值、预期、停止条件、回退值与审批状态。

方案状态使用 READY FOR REVIEW / DRAFT / HOLD / STOP;如已执行,另行记录实际结果及回读证据。未得到明确批准时,不得声称已修改线上对象。

© xjli360, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references) in amazon-skills/douyin/baize/sealeap-baize-amazon-conversion-root-cause of xjli360/sealeap-amazon-skills.

  • SKILL.md
  • agents/openai.yaml
  • references/mcp-data-plan.md
  • references/playbook.md
  • scripts/mcp_research.py

Open the folder on GitHubat commit 497d4b8

Compare with similar skills

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Self Healingpskoett/pskoett-ai-skills314—~5.3kAutomated safety check: NotesNone

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Categories

Questions about Sealeap Baize Amazon Conversion Root Cause

What does Sealeap Baize Amazon Conversion Root Cause do?

Diagnose weak Amazon conversion product-first by benchmarking comparable listings, market difficulty, price-value fit, visual differentiation, keyword precision, and placement mix. Sealeap Baize Amazon Conversion Root Cause is an agent skill from xjli360/sealeap-amazon-skills. Diagnose weak Amazon conversion product-first by benchmarking comparable listings, market difficulty, price-value fit, visual differentiation, keyword precision, and placement mix.

When should I use Sealeap Baize Amazon Conversion Root Cause?

Sealeap Baize Amazon Conversion Root Cause fits situations like: 产品转化差、广告不出单、价格还是图片问题、词不准还是商品页问题、商品页位置差; tasks that involve Root cause analysis.

How do I install Sealeap Baize Amazon Conversion Root Cause in Claude Code?

Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-baize-amazon-conversion-root-cause -a claude-code`. Or copy the skill folder (amazon-skills/douyin/baize/sealeap-baize-amazon-conversion-root-cause in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-baize-amazon-conversion-root-cause in your project. Claude Code loads it when a task matches its description.

How do I install Sealeap Baize Amazon Conversion Root Cause in Codex?

Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-baize-amazon-conversion-root-cause -a codex`. Or copy the skill folder (amazon-skills/douyin/baize/sealeap-baize-amazon-conversion-root-cause in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-baize-amazon-conversion-root-cause in your project. Codex loads it when a task matches its description.

Can I use Sealeap Baize Amazon Conversion Root Cause in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-baize-amazon-conversion-root-cause -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sealeap-baize-amazon-conversion-root-cause, .gemini/skills/sealeap-baize-amazon-conversion-root-cause, .github/skills/sealeap-baize-amazon-conversion-root-cause and .opencode/skills/sealeap-baize-amazon-conversion-root-cause in your project.

What does Sealeap Baize Amazon Conversion Root Cause need to run?

Going by SKILL.md and its folder, Sealeap Baize Amazon Conversion Root Cause needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Sealeap Baize Amazon Conversion Root Cause access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Sealeap Baize Amazon Conversion Root Cause safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Sealeap Baize Amazon Conversion Root Cause use?

Sealeap Baize Amazon Conversion Root Cause is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Sealeap Baize Amazon Conversion Root Cause use?

About 537 tokens (SKILL.md is roughly 2.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.1k tokens, read only when the agent opens those files.

What are the alternatives to Sealeap Baize Amazon Conversion Root Cause?

Skills that share tags, products or a category with Sealeap Baize Amazon Conversion Root Cause: Graph-Based Bug Tracing (tirth8205/code-review-graph, 32k stars), Octocode Code Research (bgauryy/octocode, 949 stars), Debug (agentic-community/mcp-gateway-registry, 967 stars) and Broken UI Debugger (reticlehq/reticle, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Sealeap Baize Amazon Conversion Root Cause?

xjli360 (a GitHub user) maintains it in xjli360/sealeap-amazon-skills, which has 247 GitHub stars. The repository holds 179 skills in this directory. The repository was last updated on September 28, 2026.

Source: xjli360/sealeap-amazon-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.