Codebase Management
giancarloerra/SocratiCode
Set up, index, and manage SocratiCode codebase indexing. An agent skill from giancarloerra/SocratiCode.
Plan an ad-intensive but policy-compliant Amazon launch that expands indexed and converting keyword coverage while preserving profitability and inventory guardrails.
Install Sealeap Amazon White Hat Product Ranking
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-white-hat-product-ranking -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-white-hat-product-ranking --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/qilin/sealeap-amazon-white-hat-product-ranking .claude/skills/sealeap-amazon-white-hat-product-ranking && 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-amazon-white-hat-product-ranking" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-white-hat-product-ranking into .claude/skills/sealeap-amazon-white-hat-product-ranking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-white-hat-product-ranking", 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/qilin/sealeap-amazon-white-hat-product-rankingType 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-amazon-white-hat-product-ranking -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-white-hat-product-ranking --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/qilin/sealeap-amazon-white-hat-product-ranking .agents/skills/sealeap-amazon-white-hat-product-ranking && 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-amazon-white-hat-product-ranking" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-white-hat-product-ranking into .agents/skills/sealeap-amazon-white-hat-product-ranking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-white-hat-product-ranking", 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-amazon-white-hat-product-ranking -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-white-hat-product-ranking --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/qilin/sealeap-amazon-white-hat-product-ranking .cursor/skills/sealeap-amazon-white-hat-product-ranking && 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-amazon-white-hat-product-ranking" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-white-hat-product-ranking into .cursor/skills/sealeap-amazon-white-hat-product-ranking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-white-hat-product-ranking", 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/qilin/sealeap-amazon-white-hat-product-ranking--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-amazon-white-hat-product-ranking -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-white-hat-product-ranking --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/qilin/sealeap-amazon-white-hat-product-ranking .gemini/skills/sealeap-amazon-white-hat-product-ranking && 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-amazon-white-hat-product-ranking" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-white-hat-product-ranking into .gemini/skills/sealeap-amazon-white-hat-product-ranking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-white-hat-product-ranking", 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-amazon-white-hat-product-rankingInstalls 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-amazon-white-hat-product-ranking -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/qilin/sealeap-amazon-white-hat-product-ranking .github/skills/sealeap-amazon-white-hat-product-ranking && 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-amazon-white-hat-product-ranking" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-white-hat-product-ranking into .github/skills/sealeap-amazon-white-hat-product-ranking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-white-hat-product-ranking", 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-amazon-white-hat-product-ranking -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-amazon-white-hat-product-ranking --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/qilin/sealeap-amazon-white-hat-product-ranking .opencode/skills/sealeap-amazon-white-hat-product-ranking && 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-amazon-white-hat-product-ranking" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-white-hat-product-ranking into .opencode/skills/sealeap-amazon-white-hat-product-ranking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-white-hat-product-ranking", 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-amazon-white-hat-product-ranking- GitHub stars
- 251
- Token cost
- ~531 tokens
- SKILL.md length
- 87 words
- Files
- 4 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Plan an ad-intensive but policy-compliant Amazon launch that expands indexed and converting keyword coverage while preserving profitability and inventory guardrails.
- Works in 6 steps: 确认可承接 → 扩展收录入口 → 保护转化 → …
- The user asks for a pure white-hat launch
- SKILL.md covers 目标, 适用任务, 开始前要拿到 and 不可妥协的边界, plus 4 more sections
- Runs Python scripts from its folder
What it does
Sealeap Amazon White Hat Product Ranking is an agent skill from xjli360/sealeap-amazon-skills. Plan an ad-intensive but policy-compliant Amazon launch that expands indexed and converting keyword coverage while preserving profitability and inventory guardrails. Use when the user asks for a pure white-hat launch, broad keyword coverage, when to move terms into exact campaigns, or how to combine auto, broad, product targeting, and eligible promotions. No review manipulation or ranking guarantees.
Its SKILL.md is about 530 tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/mcp-data-plan.md` and `scripts/mcp_research.py`).
It sits in AI & LLM Engineering. 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
- The user asks for a pure white-hat launch
- Broad keyword coverage
- To move terms into exact campaigns
- How to combine auto
Example prompts
- “/sealeap-amazon-white-hat-product-ranking”
Requirements
- Python 3
Workflow steps
6 steps, taken from the step headings in SKILL.md.
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 Amazon White Hat Product Ranking loads about 531 tokens when it runs, and up to ~2.1k if it reads all its reference files. Until then it costs about 111 tokens; SKILL.md has 87 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). 87 words, ~531 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-amazon-white-hat-product-ranking/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- sealeap-amazon-white-hat-product-ranking
- description
- Plan an ad-intensive but policy-compliant Amazon launch that expands indexed and converting keyword coverage while preserving profitability and inventory guardrails. Use when the user asks for a pure white-hat launch, broad keyword coverage, when to move terms into exact campaigns, or how to combine auto, broad, product targeting, and eligible promotions. No review manipulation or ranking guarantees.
Amazon 合规关键词覆盖扩张
目标
通过分层广告和真实转化扩大有效关键词覆盖，把主要出单词变成可独立管理的资产，并在成熟后收缩无效花费。
适用任务
- Listing 已具备竞争力且预算相对充足的新品。
- 希望同时扩大词量并精细管理主力词。
- 需要把促销纳入广告节奏但保持官方资格和利润边界。
开始前要拿到
- 关键词全集及头部、中部、长尾和词根分类。
- Listing readiness、库存、价格、Vine 或其他官方项目资格。
- 广告预算、促销成本、贡献利润和停止线。
缺失的数据要明确列为缺口，并把结论标成事实、估算或假设；不要补造数字。
不可妥协的边界
- 评论只能来自真实客户或符合资格的官方项目；不得安排直评、测评或评论合并。
- 不得用大规模广告数量替代相关性和预算控制。
- 促销必须符合当前官方资格与价格规则，并先核算促销后贡献利润。
- 当前 Amazon 官方政策、帮助页、账户资格和后台实际字段优先于本 Skill 中的经验框架；规则可能变化时先核验。
- 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。
- 不输出原素材的创作者身份、账号、链接、视频编号或可反查线索；当前业务证据的官方来源、采集时间和口径仍需保留。
第三方 MCP 数据
只有在本任务确实需要外部市场、竞品、关键词或公开网页证据时，才读取 references/mcp-data-plan.md，并使用 scripts/mcp_research.py。
- 先动态执行 tools/list、search-tools 和 describe，依据实时 inputSchema 构造参数，不照搬历史工具名。
- 凭证只从环境变量读取，不放进命令参数、URL、Skill、结果文件或 Git。
- tools/call 可能计费。调用前展示 Provider、工具名、无密钥参数、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。
- 第三方数据标为估算或代理证据，记录 Provider、工具、无密钥参数、查询时间和原始结果位置；失败一次后记录缺口，不反复消耗额度。
- 脱敏结果用 --output 写到 Skill 包之外的任务私有目录；不假设安装位置受仓库 .gitignore 保护，不把运行结果写入 Skill 包。
工作流
1. 确认可承接
检查商品信息、价格、库存、配送、合规和真实评价基础，未达标时先修 Listing 或产品。
2. 扩展收录入口
建立受控自动、相关词根广泛和高相似商品投放，分别定义探索对象和预算。
3. 保护转化
首轮不直接无差别冲头部词，优先覆盖中部词和高意图词根；不相关词根提前审慎否定。
4. 精准承接
当某词达到相关性、样本和利润门槛且在探索层预算不稳时，迁移到独立精准广告。
5. 分层放量
随着稳定词增多，再逐步扩展头部或更泛流量；符合资格时用官方促销做独立实验，避免同时改变过多变量。
6. 成熟收敛
按增量利润保留主力词，降低重复探索和低效广告，并持续监控库存与自然侧。
判断标准
- 广告数量由业务问题决定，不设人为数量目标。
- 每个迁移词有报告证据和去重方案。
- 放量后总利润、退货和库存仍在护栏内。
必须交付的结果
- 覆盖层、承接层和放量层架构。
- 关键词迁移与否定表。
- 促销实验和库存保护方案。
- 成熟期广告收敛计划。
结尾列出数据窗口、关键假设、证据缺口、风险和下一步；如包含待执行动作，单独放在“待批准变更”中。
© 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 3 other files (scripts, references) in amazon-skills/douyin/qilin/sealeap-amazon-white-hat-product-ranking of xjli360/sealeap-amazon-skills.
- SKILL.md
- agents/openai.yaml
- references/mcp-data-plan.md
- scripts/mcp_research.py
Open the folder on GitHubat commit 497d4b8
Compare with similar skills
Sealeap Amazon White Hat Product Ranking 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 Amazon White Hat Product Ranking this skillxjli360/sealeap-amazon-skills | 251 | — | ~531 | Automated safety check: Pass | MIT | |
| Codebase Managementgiancarloerra/SocratiCode | 3.3k | 1 repos | ~1.8k | Automated safety check: Pass | AGPL-3.0 | |
| Tool Use Data Synthesissunny-glow/Auto-BenchMax | 1.3k | — | ~3.3k | Automated safety check: Pass | None | |
| Aisafetyhotwuyoscar/AISafetyHot-Hub | 827 | — | ~1.4k | Automated safety check: Pass | Custom licence | |
| MCP Local RAGshinpr/mcp-local-rag | 412 | — | ~4.4k | Automated safety check: Pass | MIT | |
| Hugging Face LLM Trainerhuggingface/skills | 11k | 1 repos | ~7.2k | Automated safety check: Pass | Apache-2.0 |
Similar skills
Tool Use Data Synthesis
sunny-glow/Auto-BenchMax
Synthesize training data for ANY tool-use / agentic benchmark, in ANY repo.
Aisafetyhot
wuyoscar/AISafetyHot-Hub
Query AI Safety HOT news, research papers, incidents, hot topics, and daily/weekly/monthly reports through its public read-only MCP service.
MCP Local RAG
shinpr/mcp-local-rag
Searches, saves, and maintains a local document index through a local RAG MCP server.
- Official
Hugging Face LLM Trainer
huggingface/skills
Trains or fine-tunes language and vision models with TRL or Unsloth on Hugging Face Jobs cloud GPUs, then converts the results to GGUF.
Local RAG Search
nkapila6/mcp-local-rag
Efficiently perform web searches using the mcp-local-rag server with semantic similarity ranking.
More from xjli360/sealeap-amazon-skills
All 179 skills in this repoSealeap Amazon Acos Diagnostics
xjli360/sealeap-amazon-skills
Diagnose Amazon Ads ACOS with reconciled CTR, CPC, CVR, AOV, ROAS, TACOS, placement, search-term, benchmark, attribution, and contribution-margin evidence, then produce a single-variable…
Sealeap Amazon Ca Apparel Ads
xjli360/sealeap-amazon-skills
Diagnose and draft Amazon Canada apparel advertising plans with lifecycle and seasonal timing, English/French search coverage, account evidence, profitability guardrails, and approval-ready…
Sealeap Amazon Listing Optimizer
xjli360/sealeap-amazon-skills
Audit, diagnose, rewrite, creatively brief, test, and safely prepare updates for Amazon product detail pages using live marketplace and product-type requirements, verified product facts, Brand…
Sealeap Amazon Prime Day Planning
xjli360/sealeap-amazon-skills
Filter, interpret, and turn the authorized 2025 Amazon Prime Day advertising insight records into a qualified event plan without averaging incompatible slices or treating historical benchmarks as…
Sealeap Amazon Product Targeting
xjli360/sealeap-amazon-skills
Research, diagnose, and draft Amazon Ads ASIN and category product-targeting plans that complement keyword targeting, including audience expansion, competitor and category traffic, cross-sell…
Sealeap Amazon Acos Conversion Diagnostics
xjli360/sealeap-amazon-skills
Diagnose high Amazon Ads ACoS by decomposing CPC, conversion rate, price, query mix, placement mix, and sample sufficiency.
Related
Works with
Categories
Questions about Sealeap Amazon White Hat Product Ranking
What does Sealeap Amazon White Hat Product Ranking do?
Plan an ad-intensive but policy-compliant Amazon launch that expands indexed and converting keyword coverage while preserving profitability and inventory guardrails. Sealeap Amazon White Hat Product Ranking is an agent skill from xjli360/sealeap-amazon-skills. Plan an ad-intensive but policy-compliant Amazon launch that expands indexed and converting keyword coverage while preserving profitability and inventory guardrails.
When should I use Sealeap Amazon White Hat Product Ranking?
Sealeap Amazon White Hat Product Ranking fits situations like: the user asks for a pure white-hat launch; broad keyword coverage; to move terms into exact campaigns; how to combine auto.
How do I install Sealeap Amazon White Hat Product Ranking in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-white-hat-product-ranking -a claude-code`. Or copy the skill folder (amazon-skills/douyin/qilin/sealeap-amazon-white-hat-product-ranking in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-amazon-white-hat-product-ranking in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Amazon White Hat Product Ranking in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-white-hat-product-ranking -a codex`. Or copy the skill folder (amazon-skills/douyin/qilin/sealeap-amazon-white-hat-product-ranking in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-amazon-white-hat-product-ranking in your project. Codex loads it when a task matches its description.
Can I use Sealeap Amazon White Hat Product Ranking 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-amazon-white-hat-product-ranking -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-amazon-white-hat-product-ranking, .gemini/skills/sealeap-amazon-white-hat-product-ranking, .github/skills/sealeap-amazon-white-hat-product-ranking and .opencode/skills/sealeap-amazon-white-hat-product-ranking in your project.
What does Sealeap Amazon White Hat Product Ranking need to run?
Going by SKILL.md and its folder, Sealeap Amazon White Hat Product Ranking needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Amazon White Hat Product Ranking 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 Amazon White Hat Product Ranking 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 Amazon White Hat Product Ranking use?
Sealeap Amazon White Hat Product Ranking 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 Amazon White Hat Product Ranking use?
About 531 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 1.5k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Amazon White Hat Product Ranking?
Skills that share tags, products or a category with Sealeap Amazon White Hat Product Ranking: Codebase Management (giancarloerra/SocratiCode, 3.3k stars), Tool Use Data Synthesis (sunny-glow/Auto-BenchMax, 1.3k stars), Aisafetyhot (wuyoscar/AISafetyHot-Hub, 827 stars) and MCP Local RAG (shinpr/mcp-local-rag, 412 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sealeap Amazon White Hat Product Ranking?
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.