SEO Image Generator
AgriciDaniel/claude-seo
Generates Open Graph previews, blog hero images, product photos and infographics for SEO use through Gemini image tools and the banana extension.
Create evidence-backed Amazon image and A+ briefs with AI while preserving the real product's shape, color, scale, included components, and policy compliance.
Install Sealeap Baize Amazon AI Image Pipeline
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-baize-amazon-ai-image-pipeline -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-baize-amazon-ai-image-pipeline --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-ai-image-pipeline .claude/skills/sealeap-baize-amazon-ai-image-pipeline && rm -rf skills-srcUse ~/.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/
Install the "sealeap-baize-amazon-ai-image-pipeline" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-image-pipeline into .claude/skills/sealeap-baize-amazon-ai-image-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-baize-amazon-ai-image-pipeline", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-image-pipelineType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-baize-amazon-ai-image-pipeline -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-baize-amazon-ai-image-pipeline --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-image-pipeline .agents/skills/sealeap-baize-amazon-ai-image-pipeline && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "sealeap-baize-amazon-ai-image-pipeline" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-image-pipeline into .agents/skills/sealeap-baize-amazon-ai-image-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-baize-amazon-ai-image-pipeline", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-baize-amazon-ai-image-pipeline -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-baize-amazon-ai-image-pipeline --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-image-pipeline .cursor/skills/sealeap-baize-amazon-ai-image-pipeline && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "sealeap-baize-amazon-ai-image-pipeline" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-image-pipeline into .cursor/skills/sealeap-baize-amazon-ai-image-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-baize-amazon-ai-image-pipeline", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/xjli360/sealeap-amazon-skills.git --path amazon-skills/douyin/baize/sealeap-baize-amazon-ai-image-pipeline--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-baize-amazon-ai-image-pipeline -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-baize-amazon-ai-image-pipeline --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-image-pipeline .gemini/skills/sealeap-baize-amazon-ai-image-pipeline && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "sealeap-baize-amazon-ai-image-pipeline" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-image-pipeline into .gemini/skills/sealeap-baize-amazon-ai-image-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-baize-amazon-ai-image-pipeline", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-baize-amazon-ai-image-pipelineInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-baize-amazon-ai-image-pipeline -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-image-pipeline .github/skills/sealeap-baize-amazon-ai-image-pipeline && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "sealeap-baize-amazon-ai-image-pipeline" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-image-pipeline into .github/skills/sealeap-baize-amazon-ai-image-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-baize-amazon-ai-image-pipeline", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-baize-amazon-ai-image-pipeline -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-baize-amazon-ai-image-pipeline --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-image-pipeline .opencode/skills/sealeap-baize-amazon-ai-image-pipeline && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "sealeap-baize-amazon-ai-image-pipeline" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/baize/sealeap-baize-amazon-ai-image-pipeline into .opencode/skills/sealeap-baize-amazon-ai-image-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-baize-amazon-ai-image-pipeline", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
sealeap-baize-amazon-ai-image-pipeline- GitHub stars
- 251
- Token cost
- ~551 tokens
- SKILL.md length
- 130 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Create evidence-backed Amazon image and A+ briefs with AI while preserving the real product's shape, color, scale, included components, and policy compliance.
- 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。 → …
- AI做亚马逊商品图、主图差异化、副图和A+规划、评论洞察转视觉、图片测款
- 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 AI Image Pipeline is an agent skill from xjli360/sealeap-amazon-skills. Create evidence-backed Amazon image and A+ briefs with AI while preserving the real product's shape, color, scale, included components, and policy compliance. Use for AI做亚马逊商品图、主图差异化、副图和A+规划、评论洞察转视觉、图片测款. Not for fabricating the product.
Its SKILL.md is about 550 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 Media & Creative, covering Image generation. 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
- AI做亚马逊商品图、主图差异化、副图和A+规划、评论洞察转视觉、图片测款
- Tasks that involve Image generation
Example prompts
- “/sealeap-baize-amazon-ai-image-pipeline”
Requirements
- Python 3
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- 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。
- 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 AI Image Pipeline loads about 551 tokens when it runs, and up to ~2.6k if it reads all its reference files. Until then it costs about 69 tokens; SKILL.md has 130 words of instructions outside code blocks.
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). 130 words, ~551 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-baize-amazon-ai-image-pipeline/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-ai-image-pipeline
- description
- Create evidence-backed Amazon image and A+ briefs with AI while preserving the real product's shape, color, scale, included components, and policy compliance. Use for AI做亚马逊商品图、主图差异化、副图和A+规划、评论洞察转视觉、图片测款. Not for fabricating the product.
Amazon AI 商品图工作流
目标
Create evidence-backed Amazon image and A+ briefs with AI while preserving the real product's shape, color, scale, included components, and policy compliance.
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。
- 不得改变商品尺寸、颜色、结构、数量、配件或效果来提高转化。
- 公开评论抓取需遵守条款、隐私与最小化原则；优先使用自有授权数据。
先判断任务模式
- 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。
- 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
- 目标 marketplace、产品事实、品牌语气和当前政策约束
- 已授权的 Listing、关键词、评论/VOC、图片和竞品证据
- 每项数据的来源、时间、站点、样本和限制
- 人工审核人、发布边界和不可生成的声明或视觉特征
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：
- 收集产品事实、实拍素材、竞品页面和合规评论洞察。
- 提炼购买动机、异议、使用场景和一个可视化差异点。
- 先生成逐张副图和 A+ brief：目标、构图、文案、证据、素材和禁改项。
- AI 仅产出构图与效果草案，产品主体用真实照片或核准 3D 素材替换。
- 主图单独按当前站点规则审核白底、占比、文字、道具和准确性。
- 把视觉概念用于未来改款时，与当前在售 Listing 严格区分。
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：获取公开竞品页面与评论的有限样本；不得绕过登录、验证码或访问控制。
- 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
- 视觉证据板
- 逐张图片 brief
- 主图合规清单
- 实物一致性审核
- 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-ai-image-pipeline 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
Sealeap Baize Amazon AI Image Pipeline next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Sealeap Baize Amazon AI Image Pipeline this skillxjli360/sealeap-amazon-skills | 251 | — | ~551 | Automated safety check: Pass | MIT | |
| SEO Image GeneratorAgriciDaniel/claude-seo | 19k | 2 repos | ~2.1k | Automated safety check: Pass | MIT | |
| Gauntlet Loopduolahypercho/gauntlet-loop | 165 | — | ~689 | Automated safety check: Pass | MIT | |
| Blog ImageAgriciDaniel/claude-blog | 2.3k | — | ~3.4k | Automated safety check: Pass | MIT | |
| Art StyleDV0x/creative-ad-agent | 120 | — | ~477 | Automated safety check: Pass | MIT | |
| ContentGerstep/cybos | 104 | — | ~616 | Automated safety check: Pass | None |
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Questions about Sealeap Baize Amazon AI Image Pipeline
What does Sealeap Baize Amazon AI Image Pipeline do?
Create evidence-backed Amazon image and A+ briefs with AI while preserving the real product's shape, color, scale, included components, and policy compliance. Sealeap Baize Amazon AI Image Pipeline is an agent skill from xjli360/sealeap-amazon-skills. Create evidence-backed Amazon image and A+ briefs with AI while preserving the real product's shape, color, scale, included components, and policy compliance.
When should I use Sealeap Baize Amazon AI Image Pipeline?
Sealeap Baize Amazon AI Image Pipeline fits situations like: AI做亚马逊商品图、主图差异化、副图和A+规划、评论洞察转视觉、图片测款; tasks that involve Image generation.
How do I install Sealeap Baize Amazon AI Image Pipeline in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-baize-amazon-ai-image-pipeline -a claude-code`. Or copy the skill folder (amazon-skills/douyin/baize/sealeap-baize-amazon-ai-image-pipeline in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-baize-amazon-ai-image-pipeline in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Baize Amazon AI Image Pipeline in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-baize-amazon-ai-image-pipeline -a codex`. Or copy the skill folder (amazon-skills/douyin/baize/sealeap-baize-amazon-ai-image-pipeline in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-baize-amazon-ai-image-pipeline in your project. Codex loads it when a task matches its description.
Can I use Sealeap Baize Amazon AI Image Pipeline 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-ai-image-pipeline -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-ai-image-pipeline, .gemini/skills/sealeap-baize-amazon-ai-image-pipeline, .github/skills/sealeap-baize-amazon-ai-image-pipeline and .opencode/skills/sealeap-baize-amazon-ai-image-pipeline in your project.
What does Sealeap Baize Amazon AI Image Pipeline need to run?
Going by SKILL.md and its folder, Sealeap Baize Amazon AI Image Pipeline needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Baize Amazon AI Image Pipeline 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 AI Image Pipeline 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 AI Image Pipeline use?
Sealeap Baize Amazon AI Image Pipeline 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 AI Image Pipeline use?
About 551 tokens (SKILL.md is roughly 2.2k 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 2k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Baize Amazon AI Image Pipeline?
Skills that share tags, products or a category with Sealeap Baize Amazon AI Image Pipeline: SEO Image Generator (AgriciDaniel/claude-seo, 19k stars), Gauntlet Loop (duolahypercho/gauntlet-loop, 165 stars), Blog Image (AgriciDaniel/claude-blog, 2.3k stars) and Art Style (DV0x/creative-ad-agent, 120 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 AI Image Pipeline?
xjli360 (a GitHub user) maintains it in xjli360/sealeap-amazon-skills, which has 251 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.