Google Ads Landing Page Audit
nowork-studio/notfair-plugin
Scores Google Ads landing pages on five weighted dimensions and diagnoses why high-CTR ad groups convert poorly, with concrete fixes for each page.
Agent skill
Sealeap Fenghuang Amazon Prelaunch Audience Launch
Plan a compliant pre-launch audience build for a new Amazon product (US marketplace by default)—social following, email list, private community, creator seeding, live shopping—and combine it with…
Install Sealeap Fenghuang Amazon Prelaunch Audience Launch
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-fenghuang-amazon-prelaunch-audience-launch -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-fenghuang-amazon-prelaunch-audience-launch --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/youtube/fenghuang/sealeap-fenghuang-amazon-prelaunch-audience-launch .claude/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch && 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-fenghuang-amazon-prelaunch-audience-launch" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/youtube/fenghuang/sealeap-fenghuang-amazon-prelaunch-audience-launch into .claude/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-fenghuang-amazon-prelaunch-audience-launch", 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/youtube/fenghuang/sealeap-fenghuang-amazon-prelaunch-audience-launchType 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-fenghuang-amazon-prelaunch-audience-launch -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-fenghuang-amazon-prelaunch-audience-launch --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/youtube/fenghuang/sealeap-fenghuang-amazon-prelaunch-audience-launch .agents/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch && 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-fenghuang-amazon-prelaunch-audience-launch" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/youtube/fenghuang/sealeap-fenghuang-amazon-prelaunch-audience-launch into .agents/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-fenghuang-amazon-prelaunch-audience-launch", 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-fenghuang-amazon-prelaunch-audience-launch -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-fenghuang-amazon-prelaunch-audience-launch --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/youtube/fenghuang/sealeap-fenghuang-amazon-prelaunch-audience-launch .cursor/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch && 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-fenghuang-amazon-prelaunch-audience-launch" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/youtube/fenghuang/sealeap-fenghuang-amazon-prelaunch-audience-launch into .cursor/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-fenghuang-amazon-prelaunch-audience-launch", 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/youtube/fenghuang/sealeap-fenghuang-amazon-prelaunch-audience-launch--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-fenghuang-amazon-prelaunch-audience-launch -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-fenghuang-amazon-prelaunch-audience-launch --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/youtube/fenghuang/sealeap-fenghuang-amazon-prelaunch-audience-launch .gemini/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch && 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-fenghuang-amazon-prelaunch-audience-launch" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/youtube/fenghuang/sealeap-fenghuang-amazon-prelaunch-audience-launch into .gemini/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-fenghuang-amazon-prelaunch-audience-launch", 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-fenghuang-amazon-prelaunch-audience-launchInstalls 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-fenghuang-amazon-prelaunch-audience-launch -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/youtube/fenghuang/sealeap-fenghuang-amazon-prelaunch-audience-launch .github/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch && 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-fenghuang-amazon-prelaunch-audience-launch" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/youtube/fenghuang/sealeap-fenghuang-amazon-prelaunch-audience-launch into .github/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-fenghuang-amazon-prelaunch-audience-launch", 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-fenghuang-amazon-prelaunch-audience-launch -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-fenghuang-amazon-prelaunch-audience-launch --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/youtube/fenghuang/sealeap-fenghuang-amazon-prelaunch-audience-launch .opencode/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch && 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-fenghuang-amazon-prelaunch-audience-launch" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/youtube/fenghuang/sealeap-fenghuang-amazon-prelaunch-audience-launch into .opencode/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-fenghuang-amazon-prelaunch-audience-launch", 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-fenghuang-amazon-prelaunch-audience-launch- GitHub stars
- 251
- Token cost
- ~738 tokens
- SKILL.md length
- 154 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Plan a compliant pre-launch audience build for a new Amazon product (US marketplace by default)—social following, email list, private community, creator seeding, live shopping—and combine it with…
- 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。 → …
- 新品怎么首发、站外引流、上架前预热、邮件列表怎么用、找达人推广、首发用不用广告、首发抓大放小
- 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 Fenghuang Amazon Prelaunch Audience Launch is an agent skill from xjli360/sealeap-amazon-skills. Plan a compliant pre-launch audience build for a new Amazon product (US marketplace by default)—social following, email list, private community, creator seeding, live shopping—and combine it with launch-week PPC and truthful persuasion cues (scarcity, social proof, authority) while excluding any incentivized-review tactic. Use for 新品怎么首发、站外引流、上架前预热、邮件列表怎么用、找达人推广、首发用不用广告、首发抓大放小. Do not use to plan giveaways-for-reviews, search-find-buy, or any incentivized review scheme.
Its SKILL.md is about 740 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 Marketing & SEO, covering Marketing psychology and Paid advertising. 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
- 新品怎么首发、站外引流、上架前预热、邮件列表怎么用、找达人推广、首发用不用广告、首发抓大放小
- Plan giveaways-for-reviews
- Search-find-buy
- Any incentivized review scheme
Example prompts
- “/sealeap-fenghuang-amazon-prelaunch-audience-launch”
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 Fenghuang Amazon Prelaunch Audience Launch loads about 738 tokens when it runs, and up to ~3.1k if it reads all its reference files. Until then it costs about 131 tokens; SKILL.md has 154 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). 154 words, ~738 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- sealeap-fenghuang-amazon-prelaunch-audience-launch
- description
- Plan a compliant pre-launch audience build for a new Amazon product (US marketplace by default)—social following, email list, private community, creator seeding, live shopping—and combine it with launch-week PPC and truthful persuasion cues (scarcity, social proof, authority) while excluding any incentivized-review tactic. Use for 新品怎么首发、站外引流、上架前预热、邮件列表怎么用、找达人推广、首发用不用广告、首发抓大放小. Do not use to plan giveaways-for-reviews, search-find-buy, or any incentivized review scheme.
Amazon 新品站外预热与首发流量组合
目标
Plan a compliant pre-launch audience build for a new Amazon product (US marketplace by default)—social following, email list, private community, creator seeding, live shopping—and combine it with launch-week PPC and truthful persuasion cues (scarcity, social proof, authority) while excluding any incentivized-review tactic.
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。
- 默认只读诊断和草案；任何广告、Listing、库存、促销或外部系统写操作都需逐项展示并取得明确批准。
- 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。
- 来源提到的抽奖换评论、让路人「搜索-找到-购买」并留好评等做法违反平台政策，不采用；Vine 是唯一建议的早期评论渠道。
- 「站外销量激增会被推到搜索前列」是来源对算法的解释，只作待验证假设；用 Attribution 与自然排名跟踪去验证。
- 稀缺与限量信息必须真实（真的限量、真的到期），否则违反广告与消费者保护规则。
- 来源中的达人平台推荐不采纳；直播购物功能的可用性与资格以当前站点政策为准。
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
- marketplace、ASIN/SKU、产品事实与目标购买任务
- 关键词、商品投放、展示和视频的聚合表现
- 受众包定义、资格、站点限制和隐私边界
- 价格、评论、页面、库存与转化基线
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：
- 在库存到仓前留出足够预热窗口（按品类与备货周期校准）：至少一个社媒账号持续发产品诞生过程，用钩子把关注者引导进邮件列表或私域社群。
- 邮件列表运营：预热期发进度与教育内容建立信任，首发日发限时限量通知；记录打开率、点击率与到达 Listing 的比例。
- 私域社群预热：让潜在买家参与包装、口味等决定以提升参与感；首发时公告上架，不附带任何评论要求。
- 达人合作：通过达人平台类别或人工搜索找受众匹配的创作者，寄样并约定内容形式（社媒帖、视频、平台直播）；用 Attribution 链接分渠道追踪成交。
- 首发周 PPC：新品无评论时转化偏低，用较小预算测试核心词并与站外流量叠加；库存不足时先限流而不是硬推。
- 用说服原则设计首发信息：限量折扣（稀缺）、创作者背书（权威）、用户故事（社会认同）、品牌介绍视频（喜好）；每条都必须真实可证。
- 抓大放小复盘：按 Attribution 与广告报告比较各渠道成交与成本，保留效果最好的两三条渠道进入下一次首发模板。
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：获取受众匹配的公开创作者与竞品站外内容的代理观测。
- 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
- 预热时间线
- 邮件与社群内容计划
- 达人寄样与追踪表
- 首发周广告与库存方案
- 渠道效果复盘表
- 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/youtube/fenghuang/sealeap-fenghuang-amazon-prelaunch-audience-launch 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 Fenghuang Amazon Prelaunch Audience Launch 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 Fenghuang Amazon Prelaunch Audience Launch this skillxjli360/sealeap-amazon-skills | 251 | — | ~738 | Automated safety check: Pass | MIT | |
| Google Ads Landing Page Auditnowork-studio/notfair-plugin | 3.9k | — | ~306 | Automated safety check: Pass | MIT | |
| Google AdsTheMattBerman/google-ads-copilot | 238 | — | ~4.1k | Automated safety check: Pass | MIT | |
| SEO Vs AdsRyze-AI-Adgent/open-seo-mcp-skills | 4.7k | — | ~594 | Automated safety check: Pass | MIT | |
| Google Ads AuditTheMattBerman/google-ads-copilot | 238 | — | ~2.7k | Automated safety check: Pass | MIT | |
| Paid Ads Integrationsnowork-studio/notfair-plugin | 3.9k | — | ~256 | Automated safety check: Pass | MIT |
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Questions about Sealeap Fenghuang Amazon Prelaunch Audience Launch
What does Sealeap Fenghuang Amazon Prelaunch Audience Launch do?
Plan a compliant pre-launch audience build for a new Amazon product (US marketplace by default)—social following, email list, private community, creator seeding, live shopping—and combine it with…. Sealeap Fenghuang Amazon Prelaunch Audience Launch is an agent skill from xjli360/sealeap-amazon-skills. Plan a compliant pre-launch audience build for a new Amazon product (US marketplace by default)—social following, email list, private community, creator seeding, live shopping—and combine it with launch-week PPC and truthful persuasion cues (scarcity, social proof, authority) while excluding any incentivized-review tactic.
When should I use Sealeap Fenghuang Amazon Prelaunch Audience Launch?
Sealeap Fenghuang Amazon Prelaunch Audience Launch fits situations like: 新品怎么首发、站外引流、上架前预热、邮件列表怎么用、找达人推广、首发用不用广告、首发抓大放小; plan giveaways-for-reviews; search-find-buy; any incentivized review scheme.
How do I install Sealeap Fenghuang Amazon Prelaunch Audience Launch in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-fenghuang-amazon-prelaunch-audience-launch -a claude-code`. Or copy the skill folder (amazon-skills/youtube/fenghuang/sealeap-fenghuang-amazon-prelaunch-audience-launch in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Fenghuang Amazon Prelaunch Audience Launch in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-fenghuang-amazon-prelaunch-audience-launch -a codex`. Or copy the skill folder (amazon-skills/youtube/fenghuang/sealeap-fenghuang-amazon-prelaunch-audience-launch in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch in your project. Codex loads it when a task matches its description.
Can I use Sealeap Fenghuang Amazon Prelaunch Audience Launch 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-fenghuang-amazon-prelaunch-audience-launch -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-fenghuang-amazon-prelaunch-audience-launch, .gemini/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch, .github/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch and .opencode/skills/sealeap-fenghuang-amazon-prelaunch-audience-launch in your project.
What does Sealeap Fenghuang Amazon Prelaunch Audience Launch need to run?
Going by SKILL.md and its folder, Sealeap Fenghuang Amazon Prelaunch Audience Launch needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Fenghuang Amazon Prelaunch Audience Launch 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 Fenghuang Amazon Prelaunch Audience Launch 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 Fenghuang Amazon Prelaunch Audience Launch use?
Sealeap Fenghuang Amazon Prelaunch Audience Launch 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 Fenghuang Amazon Prelaunch Audience Launch use?
About 738 tokens (SKILL.md is roughly 3k 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 2.4k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Fenghuang Amazon Prelaunch Audience Launch?
Skills that share tags, products or a category with Sealeap Fenghuang Amazon Prelaunch Audience Launch: Google Ads Landing Page Audit (nowork-studio/notfair-plugin, 3.9k stars), Google Ads (TheMattBerman/google-ads-copilot, 238 stars), SEO Vs Ads (Ryze-AI-Adgent/open-seo-mcp-skills, 4.7k stars) and Google Ads Audit (TheMattBerman/google-ads-copilot, 238 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sealeap Fenghuang Amazon Prelaunch Audience Launch?
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.