.NET MAUI Release Readiness
dotnet/maui
Produces evidence-backed ship-readiness verdicts for .NET MAUI Servicing Releases and Previews, and drafts public-safe release handoff pages from the result.
Agent skill
Sealeap Hundun Amazon Launch Review Rank Playbook
Sequence a new listing's launch into review-seeding, rank-building, ad-structuring and assortment-differentiation phases, each with an evidence check and a go/no-go signal, targeting a sub-category…
Install Sealeap Hundun Amazon Launch Review Rank Playbook
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-hundun-amazon-launch-review-rank-playbook -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-hundun-amazon-launch-review-rank-playbook --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/bilibili/hundun/sealeap-hundun-amazon-launch-review-rank-playbook .claude/skills/sealeap-hundun-amazon-launch-review-rank-playbook && 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-hundun-amazon-launch-review-rank-playbook" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/hundun/sealeap-hundun-amazon-launch-review-rank-playbook into .claude/skills/sealeap-hundun-amazon-launch-review-rank-playbook/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-hundun-amazon-launch-review-rank-playbook", 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/bilibili/hundun/sealeap-hundun-amazon-launch-review-rank-playbookType 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-hundun-amazon-launch-review-rank-playbook -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-hundun-amazon-launch-review-rank-playbook --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/bilibili/hundun/sealeap-hundun-amazon-launch-review-rank-playbook .agents/skills/sealeap-hundun-amazon-launch-review-rank-playbook && 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-hundun-amazon-launch-review-rank-playbook" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/hundun/sealeap-hundun-amazon-launch-review-rank-playbook into .agents/skills/sealeap-hundun-amazon-launch-review-rank-playbook/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-hundun-amazon-launch-review-rank-playbook", 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-hundun-amazon-launch-review-rank-playbook -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-hundun-amazon-launch-review-rank-playbook --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/bilibili/hundun/sealeap-hundun-amazon-launch-review-rank-playbook .cursor/skills/sealeap-hundun-amazon-launch-review-rank-playbook && 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-hundun-amazon-launch-review-rank-playbook" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/hundun/sealeap-hundun-amazon-launch-review-rank-playbook into .cursor/skills/sealeap-hundun-amazon-launch-review-rank-playbook/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-hundun-amazon-launch-review-rank-playbook", 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/bilibili/hundun/sealeap-hundun-amazon-launch-review-rank-playbook--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-hundun-amazon-launch-review-rank-playbook -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-hundun-amazon-launch-review-rank-playbook --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/bilibili/hundun/sealeap-hundun-amazon-launch-review-rank-playbook .gemini/skills/sealeap-hundun-amazon-launch-review-rank-playbook && 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-hundun-amazon-launch-review-rank-playbook" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/hundun/sealeap-hundun-amazon-launch-review-rank-playbook into .gemini/skills/sealeap-hundun-amazon-launch-review-rank-playbook/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-hundun-amazon-launch-review-rank-playbook", 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-hundun-amazon-launch-review-rank-playbookInstalls 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-hundun-amazon-launch-review-rank-playbook -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/bilibili/hundun/sealeap-hundun-amazon-launch-review-rank-playbook .github/skills/sealeap-hundun-amazon-launch-review-rank-playbook && 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-hundun-amazon-launch-review-rank-playbook" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/hundun/sealeap-hundun-amazon-launch-review-rank-playbook into .github/skills/sealeap-hundun-amazon-launch-review-rank-playbook/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-hundun-amazon-launch-review-rank-playbook", 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-hundun-amazon-launch-review-rank-playbook -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-hundun-amazon-launch-review-rank-playbook --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/bilibili/hundun/sealeap-hundun-amazon-launch-review-rank-playbook .opencode/skills/sealeap-hundun-amazon-launch-review-rank-playbook && 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-hundun-amazon-launch-review-rank-playbook" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/hundun/sealeap-hundun-amazon-launch-review-rank-playbook into .opencode/skills/sealeap-hundun-amazon-launch-review-rank-playbook/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-hundun-amazon-launch-review-rank-playbook", 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-hundun-amazon-launch-review-rank-playbook- GitHub stars
- 251
- Token cost
- ~895 tokens
- SKILL.md length
- 174 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Sequence a new listing's launch into review-seeding, rank-building, ad-structuring and assortment-differentiation phases, each with an evidence check and a go/no-go signal, targeting a sub-category…
- 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。 → …
- 新品怎么打爆、新品期目标怎么定、要不要做站外折扣冲评论、新品广告怎么分组、变体怎么做差异化
- 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 Hundun Amazon Launch Review Rank Playbook is an agent skill from xjli360/sealeap-amazon-skills. Sequence a new listing's launch into review-seeding, rank-building, ad-structuring and assortment-differentiation phases, each with an evidence check and a go/no-go signal, targeting a sub-category rank band and a review-count threshold benchmarked against the current category's own weakest qualifying listings rather than a fixed number. Any cross-listing causal or algorithmic claim stays flagged as an account-level hypothesis pending verification. Use for 新品怎么打爆、新品期目标怎么定、要不要做站外折扣冲评论、新品广告怎么分组、变体怎么做差异化. Do not use…
Its SKILL.md is about 900 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 Product & Project Management, covering Feature launches and release readiness. 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
- 新品怎么打爆、新品期目标怎么定、要不要做站外折扣冲评论、新品广告怎么分组、变体怎么做差异化
- Justify review manipulation
- Any incentivized-for-positive-review arrangement
- Do not treat any phase budget
Example prompts
- “/sealeap-hundun-amazon-launch-review-rank-playbook”
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 Hundun Amazon Launch Review Rank Playbook loads about 895 tokens when it runs, and up to ~3.5k if it reads all its reference files. Until then it costs about 185 tokens; SKILL.md has 174 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). 174 words, ~895 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-hundun-amazon-launch-review-rank-playbook/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- sealeap-hundun-amazon-launch-review-rank-playbook
- description
- Sequence a new listing's launch into review-seeding, rank-building, ad-structuring and assortment-differentiation phases, each with an evidence check and a go/no-go signal, targeting a sub-category rank band and a review-count threshold benchmarked against the current category's own weakest qualifying listings rather than a fixed number. Any cross-listing causal or algorithmic claim stays flagged as an account-level hypothesis pending verification. Use for 新品怎么打爆、新品期目标怎么定、要不要做站外折扣冲评论、新品广告怎么分组、变体怎么做差异化. Do not use to justify review manipulation, paid reviews, or any incentivized-for-positive-review arrangement; do not treat any phase budget or conversion figure below as a fixed rule.
Amazon 新品冲榜与评论积累打法
目标
Sequence a new listing's launch into review-seeding, rank-building, ad-structuring and assortment-differentiation phases, each with an evidence check and a go/no-go signal, targeting a sub-category rank band and a review-count threshold benchmarked against the current category's own weakest qualifying listings rather than a fixed number. Any cross-listing causal or algorithmic claim stays flagged as an account-level hypothesis pending verification.
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。
- 阶段目标里的具体评论数量、折扣力度、出单速度等均为来源经验值，必须用当前账户所在类目、当前时点的 BSR/新品榜实际数据重新校准，不能直接套用固定数字。
- 站外限时折扣加速排名与评论积累的效果、以及“经过站外折扣的订单索评回复率更高”这一说法，均为账户内观察到的经验，属于待验证假设，不同类目/客群可能表现不同。
- 任何形式的刷单、付费换好评、虚假交易不在本方法适用范围内；本方法仅覆盖真实成交基础上的合规让利与合规索评。
- “一个店铺只聚焦一到两个类目、两三款核心 listing”是来源给出的经验取舍，实际聚焦程度应结合团队精力、供应链掌控力与现金流综合判断，不是绝对规则。
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 与案例 ASIN 的明确时间范围
- 销量、评论、价格、促销、变体和上架时间线
- 关键词自然/广告可见度、品牌与站外流量代理证据
- 可复核来源、数据口径、缺失项和替代解释
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：
- 先用同类目 BSR 前列与新品榜中评论数最少的若干条 listing，估算出“进入这个小类需要的评论量门槛”和“目标排名区间”，作为本次新品的阶段性目标，而不是直接对标头部大卖家。
- 阶段一：善用平台官方的合规索评渠道（如允许卖家赠送样品换取早期评论的官方计划）获取第一批基础评论；若这批评论的平均分明显偏低，先评估产品本身能否改进，改不动就趁早止损换品。
- 阶段二：如果评估后决定推进，可用不在 listing 页面展示、只在站外渠道发放的限时折扣，配合请求评论动作来加速排名与评论积累；必须持续监测站外折扣的出单速度，连续放不完说明需求不足，应及时停止并更换产品，而不是加大折扣力度硬撑。
- 阶段三：围绕该 listing 建立自动广告、精准手动广告、低价广泛匹配广告三个广告组的基础结构，把自然转化最好的词补进标题、五点与后台关键词，用关键词覆盖数与自然流量趋势是否持续增长作为是否继续当前打法的判断依据。
- 阶段四：排名和评论积累到一定程度后再做变体差异化——用一个变体做价格竞争力最强的引流款，用其余变体做正常利润款，并评估哪些变体可自主设计以形成竞争壁垒。
- 全程执行前先测算所需备货量与预算是否可承受（含索评赠品和折扣损耗），评估不可接受就调低目标节奏或更换风险更低的产品，避免多品类分散精力导致每个 listing 都做不透。
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：补充同类目 BSR 前列与新品榜的评论数量分布等第三方观测数据，用于校准新品进入门槛与目标排名区间。
- 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
- 类目排名与评论门槛测算表
- 四阶段推进计划（含止损条件）
- 广告组结构记录（自动/精准手动/低价广泛匹配）
- 变体差异化与角色分工表（引流款/利润款）
- 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/bilibili/hundun/sealeap-hundun-amazon-launch-review-rank-playbook 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 Hundun Amazon Launch Review Rank Playbook 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 Hundun Amazon Launch Review Rank Playbook this skillxjli360/sealeap-amazon-skills | 251 | — | ~895 | Automated safety check: Pass | MIT | |
| .NET MAUI Release Readinessdotnet/maui | 23k | — | ~15k | Automated safety check: Pass | MIT | |
| Release ValidationMesh-LLM/mesh-llm | 3.5k | — | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| Final Release Reviewopenai/openai-agents-python | 30k | — | ~5.4k | Automated safety check: Pass | MIT | |
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| Acceptance Demo GeneratorChachamaru127/claude-code-harness | 3.2k | — | ~3.4k | Automated safety check: Notes | MIT |
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Questions about Sealeap Hundun Amazon Launch Review Rank Playbook
What does Sealeap Hundun Amazon Launch Review Rank Playbook do?
Sequence a new listing's launch into review-seeding, rank-building, ad-structuring and assortment-differentiation phases, each with an evidence check and a go/no-go signal, targeting a sub-category…. Sealeap Hundun Amazon Launch Review Rank Playbook is an agent skill from xjli360/sealeap-amazon-skills. Sequence a new listing's launch into review-seeding, rank-building, ad-structuring and assortment-differentiation phases, each with an evidence check and a go/no-go signal, targeting a sub-category rank band and a review-count threshold benchmarked against the current category's own weakest qualifying listings rather than a fixed number.
When should I use Sealeap Hundun Amazon Launch Review Rank Playbook?
Sealeap Hundun Amazon Launch Review Rank Playbook fits situations like: 新品怎么打爆、新品期目标怎么定、要不要做站外折扣冲评论、新品广告怎么分组、变体怎么做差异化; justify review manipulation; any incentivized-for-positive-review arrangement; do not treat any phase budget.
How do I install Sealeap Hundun Amazon Launch Review Rank Playbook in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-hundun-amazon-launch-review-rank-playbook -a claude-code`. Or copy the skill folder (amazon-skills/bilibili/hundun/sealeap-hundun-amazon-launch-review-rank-playbook in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-hundun-amazon-launch-review-rank-playbook in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Hundun Amazon Launch Review Rank Playbook in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-hundun-amazon-launch-review-rank-playbook -a codex`. Or copy the skill folder (amazon-skills/bilibili/hundun/sealeap-hundun-amazon-launch-review-rank-playbook in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-hundun-amazon-launch-review-rank-playbook in your project. Codex loads it when a task matches its description.
Can I use Sealeap Hundun Amazon Launch Review Rank Playbook 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-hundun-amazon-launch-review-rank-playbook -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-hundun-amazon-launch-review-rank-playbook, .gemini/skills/sealeap-hundun-amazon-launch-review-rank-playbook, .github/skills/sealeap-hundun-amazon-launch-review-rank-playbook and .opencode/skills/sealeap-hundun-amazon-launch-review-rank-playbook in your project.
What does Sealeap Hundun Amazon Launch Review Rank Playbook need to run?
Going by SKILL.md and its folder, Sealeap Hundun Amazon Launch Review Rank Playbook needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Hundun Amazon Launch Review Rank Playbook 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 Hundun Amazon Launch Review Rank Playbook 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 Hundun Amazon Launch Review Rank Playbook use?
Sealeap Hundun Amazon Launch Review Rank Playbook 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 Hundun Amazon Launch Review Rank Playbook use?
About 895 tokens (SKILL.md is roughly 3.6k 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 2.6k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Hundun Amazon Launch Review Rank Playbook?
Skills that share tags, products or a category with Sealeap Hundun Amazon Launch Review Rank Playbook: .NET MAUI Release Readiness (dotnet/maui, 23k stars), Release Validation (Mesh-LLM/mesh-llm, 3.5k stars), Final Release Review (openai/openai-agents-python, 30k stars) and Final Release Review (openai/openai-agents-js, 3.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sealeap Hundun Amazon Launch Review Rank Playbook?
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.