Launchfast Full Research Loop
LeoYeAI/openclaw-master-skills
Complete Amazon FBA product research pipeline using the LaunchFast MCP.
Agent skill
Sealeap Dijiang Amazon Conversion Rate Keyword Filter
Filter and prioritize keywords by historical conversion rate and market-concentration signals rather than raw search volume alone, manually verify each candidate phrase against live search results…
Install Sealeap Dijiang Amazon Conversion Rate Keyword Filter
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-dijiang-amazon-conversion-rate-keyword-filter -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-dijiang-amazon-conversion-rate-keyword-filter --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/dijiang/sealeap-dijiang-amazon-conversion-rate-keyword-filter .claude/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter && 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-dijiang-amazon-conversion-rate-keyword-filter" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/youtube/dijiang/sealeap-dijiang-amazon-conversion-rate-keyword-filter into .claude/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-dijiang-amazon-conversion-rate-keyword-filter", 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/dijiang/sealeap-dijiang-amazon-conversion-rate-keyword-filterType 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-dijiang-amazon-conversion-rate-keyword-filter -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-dijiang-amazon-conversion-rate-keyword-filter --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/dijiang/sealeap-dijiang-amazon-conversion-rate-keyword-filter .agents/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter && 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-dijiang-amazon-conversion-rate-keyword-filter" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/youtube/dijiang/sealeap-dijiang-amazon-conversion-rate-keyword-filter into .agents/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-dijiang-amazon-conversion-rate-keyword-filter", 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-dijiang-amazon-conversion-rate-keyword-filter -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-dijiang-amazon-conversion-rate-keyword-filter --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/dijiang/sealeap-dijiang-amazon-conversion-rate-keyword-filter .cursor/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter && 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-dijiang-amazon-conversion-rate-keyword-filter" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/youtube/dijiang/sealeap-dijiang-amazon-conversion-rate-keyword-filter into .cursor/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-dijiang-amazon-conversion-rate-keyword-filter", 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/dijiang/sealeap-dijiang-amazon-conversion-rate-keyword-filter--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-dijiang-amazon-conversion-rate-keyword-filter -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-dijiang-amazon-conversion-rate-keyword-filter --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/dijiang/sealeap-dijiang-amazon-conversion-rate-keyword-filter .gemini/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter && 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-dijiang-amazon-conversion-rate-keyword-filter" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/youtube/dijiang/sealeap-dijiang-amazon-conversion-rate-keyword-filter into .gemini/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-dijiang-amazon-conversion-rate-keyword-filter", 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-dijiang-amazon-conversion-rate-keyword-filterInstalls 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-dijiang-amazon-conversion-rate-keyword-filter -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/dijiang/sealeap-dijiang-amazon-conversion-rate-keyword-filter .github/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter && 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-dijiang-amazon-conversion-rate-keyword-filter" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/youtube/dijiang/sealeap-dijiang-amazon-conversion-rate-keyword-filter into .github/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-dijiang-amazon-conversion-rate-keyword-filter", 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-dijiang-amazon-conversion-rate-keyword-filter -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-dijiang-amazon-conversion-rate-keyword-filter --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/dijiang/sealeap-dijiang-amazon-conversion-rate-keyword-filter .opencode/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter && 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-dijiang-amazon-conversion-rate-keyword-filter" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/youtube/dijiang/sealeap-dijiang-amazon-conversion-rate-keyword-filter into .opencode/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-dijiang-amazon-conversion-rate-keyword-filter", 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-dijiang-amazon-conversion-rate-keyword-filter- GitHub stars
- 251
- Token cost
- ~768 tokens
- SKILL.md length
- 142 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Filter and prioritize keywords by historical conversion rate and market-concentration signals rather than raw search volume alone, manually verify each candidate phrase against live search results…
- 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。 → …
- 大词好还是长尾词好、关键词该放正文还是后台、怎么判断一个词值不值得砸广告
- 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 Dijiang Amazon Conversion Rate Keyword Filter is an agent skill from xjli360/sealeap-amazon-skills. Filter and prioritize keywords by historical conversion rate and market-concentration signals rather than raw search volume alone, manually verify each candidate phrase against live search results for genuine relevance, and split the surviving list into primary listing/PPC terms versus backend-only indexing terms. Use for 大词好还是长尾词好、关键词该放正文还是后台、怎么判断一个词值不值得砸广告. Do not use to treat any third-party conversion-rate or market-availability metric as an Amazon-confirmed fact — treat it as a vendor-specific estimate.
Its SKILL.md is about 770 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 Conversion rate optimization, Keyword research 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
- 大词好还是长尾词好、关键词该放正文还是后台、怎么判断一个词值不值得砸广告
- Treat any third-party conversion-rate
- Market-availability metric as an Amazon-confirmed fact — treat it as a vendor-specific estimate
Example prompts
- “/sealeap-dijiang-amazon-conversion-rate-keyword-filter”
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 Dijiang Amazon Conversion Rate Keyword Filter loads about 768 tokens when it runs, and up to ~3.2k if it reads all its reference files. Until then it costs about 142 tokens; SKILL.md has 142 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). 142 words, ~768 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- sealeap-dijiang-amazon-conversion-rate-keyword-filter
- description
- Filter and prioritize keywords by historical conversion rate and market-concentration signals rather than raw search volume alone, manually verify each candidate phrase against live search results for genuine relevance, and split the surviving list into primary listing/PPC terms versus backend-only indexing terms. Use for 大词好还是长尾词好、关键词该放正文还是后台、怎么判断一个词值不值得砸广告. Do not use to treat any third-party conversion-rate or market-availability metric as an Amazon-confirmed fact — treat it as a vendor-specific estimate.
Amazon 转化率优先关键词筛选
目标
Filter and prioritize keywords by historical conversion rate and market-concentration signals rather than raw search volume alone, manually verify each candidate phrase against live search results for genuine relevance, and split the surviving list into primary listing/PPC terms versus backend-only indexing terms.
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。
- 转化率、市场集中度、动销效率等指标均来自第三方工具的历史估算，口径与算法不透明，属于前台观测代理指标，不等同于平台内部真实成交数据。
- 固定的转化率或集中度分界百分比是来源给出的个人经验值，需按自身类目重新校准，不同价格带、不同类目的合理区间差异很大。
- 人工核验搜索结果相关性会受个性化、地域与登录状态影响，同一账号多次核验结果可能有差异，建议多次或换环境交叉确认后再下结论。
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、产品事实、ASIN/SKU 与目标购买意图
- 本品和可比竞品的关键词、自然位置、广告可见度与采样时间
- 搜索词报告、转化、CPC、订单、利润和 Listing 当前覆盖
- 站点语言、变体、价格、库存与同期促销记录
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：
- 建立候选词池时不要默认搜索量越大越该用，改为同时纳入该词的历史成交转化率与市场集中度（该细分需求中头部几家卖家吃掉了多少比例的成交量）两个维度，与按搜索量排序取词的常见做法形成对照，两种口径可以并行比较，不必二选一。
- 优先保留转化率较高、且头部卖家集中度不算太高的词，而不是只看绝对搜索量大小；转化率与集中度的具体分界线按自身类目与竞争格局设定，不套用某个固定百分比。
- 对第三方工具给出的预计需要多少动销量才能自然进入首页一类效率指标，只作为在多个候选词之间比较相对难度的参考，不当作精确可实现的承诺。
- 汇总出候选词表后逐词到搜索结果里人工核验：实际搜索该词组时排在前面的商品是否真的与自己商品是同一类，若结果里大量是不相关商品，说明这个词字面相关但购买意图不匹配，标记为仅索引不主推。
- 把通过人工核验、转化与集中度表现俱佳的词标记为主力词，用于Listing正文与广告重点投放；把相关性不足或效率指标较差、但仍有一定关联的词标记为仅后台索引，只放入后台关键词字段。
- 定期用同一套口径复核主力词清单，因为转化率与集中度会随季节、竞品变化而改变，不作为一次性结论长期沿用。
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：获取候选关键词的历史成交转化率与市场集中度等第三方估算指标，作为按搜索量排序之外的补充筛选证据。
- 先
doctor，再search-tools和describe；工具名及参数以实时tools/list与inputSchema为准。 - Token 只从环境变量读取。不得写入命令参数、URL、Skill、报告、日志或 Git。
tools/call或 Actor 可能计费；先展示 Provider、工具、无密钥业务参数、预计成本与输出位置，核对已有授权覆盖后才加--allow-cost；该标志不是费用上限。
必须交付的结果
- 转化率与市场集中度双维度候选词表
- 逐词搜索结果相关性人工核验记录
- 主力词/仅索引词分层清单
- 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/dijiang/sealeap-dijiang-amazon-conversion-rate-keyword-filter 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 Dijiang Amazon Conversion Rate Keyword Filter 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 Dijiang Amazon Conversion Rate Keyword Filter this skillxjli360/sealeap-amazon-skills | 251 | — | ~768 | Automated safety check: Pass | MIT | |
| Launchfast Full Research LoopLeoYeAI/openclaw-master-skills | 2.2k | — | ~4.5k | Automated safety check: Pass | MIT | |
| Launchfast Full Research Loophashgraph-online/awesome-codex-plugins | 1.3k | — | ~657 | Automated safety check: Pass | Apache-2.0 | |
| Launchfast Ppc Researchhashgraph-online/awesome-codex-plugins | 1.3k | — | ~784 | Automated safety check: Pass | Apache-2.0 | |
| Google Ads Landing Page Auditnowork-studio/notfair-plugin | 3.9k | — | ~306 | Automated safety check: Pass | MIT | |
| 03 Danh Gia Hieu Suatminhnv0807/ai-business-skills | 609 | — | ~4.6k | Automated safety check: Pass | MIT |
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Questions about Sealeap Dijiang Amazon Conversion Rate Keyword Filter
What does Sealeap Dijiang Amazon Conversion Rate Keyword Filter do?
Filter and prioritize keywords by historical conversion rate and market-concentration signals rather than raw search volume alone, manually verify each candidate phrase against live search results…. Sealeap Dijiang Amazon Conversion Rate Keyword Filter is an agent skill from xjli360/sealeap-amazon-skills. Filter and prioritize keywords by historical conversion rate and market-concentration signals rather than raw search volume alone, manually verify each candidate phrase against live search results for genuine relevance, and split the surviving list into primary listing/PPC terms versus backend-only indexing terms.
When should I use Sealeap Dijiang Amazon Conversion Rate Keyword Filter?
Sealeap Dijiang Amazon Conversion Rate Keyword Filter fits situations like: 大词好还是长尾词好、关键词该放正文还是后台、怎么判断一个词值不值得砸广告; treat any third-party conversion-rate; market-availability metric as an Amazon-confirmed fact — treat it as a vendor-specific estimate.
How do I install Sealeap Dijiang Amazon Conversion Rate Keyword Filter in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-dijiang-amazon-conversion-rate-keyword-filter -a claude-code`. Or copy the skill folder (amazon-skills/youtube/dijiang/sealeap-dijiang-amazon-conversion-rate-keyword-filter in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Dijiang Amazon Conversion Rate Keyword Filter in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-dijiang-amazon-conversion-rate-keyword-filter -a codex`. Or copy the skill folder (amazon-skills/youtube/dijiang/sealeap-dijiang-amazon-conversion-rate-keyword-filter in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter in your project. Codex loads it when a task matches its description.
Can I use Sealeap Dijiang Amazon Conversion Rate Keyword Filter 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-dijiang-amazon-conversion-rate-keyword-filter -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-dijiang-amazon-conversion-rate-keyword-filter, .gemini/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter, .github/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter and .opencode/skills/sealeap-dijiang-amazon-conversion-rate-keyword-filter in your project.
What does Sealeap Dijiang Amazon Conversion Rate Keyword Filter need to run?
Going by SKILL.md and its folder, Sealeap Dijiang Amazon Conversion Rate Keyword Filter needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Dijiang Amazon Conversion Rate Keyword Filter 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 Dijiang Amazon Conversion Rate Keyword Filter 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 Dijiang Amazon Conversion Rate Keyword Filter use?
Sealeap Dijiang Amazon Conversion Rate Keyword Filter 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 Dijiang Amazon Conversion Rate Keyword Filter use?
About 768 tokens (SKILL.md is roughly 3.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.5k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Dijiang Amazon Conversion Rate Keyword Filter?
Skills that share tags, products or a category with Sealeap Dijiang Amazon Conversion Rate Keyword Filter: Launchfast Full Research Loop (LeoYeAI/openclaw-master-skills, 2.2k stars), Launchfast Full Research Loop (hashgraph-online/awesome-codex-plugins, 1.3k stars), Launchfast Ppc Research (hashgraph-online/awesome-codex-plugins, 1.3k stars) and Google Ads Landing Page Audit (nowork-studio/notfair-plugin, 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 Dijiang Amazon Conversion Rate Keyword Filter?
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.