Asd Ste100
danyuchn/asd-ste100-skill
A skill your agent uses when English text must be parsed without a human to resolve ambiguity — tool descriptions, error messages, inter-agent instructions, system prompts, status reports — and…
Agent skill
Sealeap Bifang Amazon Keyword Optimization Loop
Run a five-stage keyword workflow for an Amazon listing: collect candidate terms from several comparable ASINs, screen them by product-fact relevance and observed performance, embed the shortlist…
Install Sealeap Bifang Amazon Keyword Optimization Loop
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-bifang-amazon-keyword-optimization-loop -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-bifang-amazon-keyword-optimization-loop --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/bifang/sealeap-bifang-amazon-keyword-optimization-loop .claude/skills/sealeap-bifang-amazon-keyword-optimization-loop && 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-bifang-amazon-keyword-optimization-loop" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/bifang/sealeap-bifang-amazon-keyword-optimization-loop into .claude/skills/sealeap-bifang-amazon-keyword-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-bifang-amazon-keyword-optimization-loop", 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/bifang/sealeap-bifang-amazon-keyword-optimization-loopType 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-bifang-amazon-keyword-optimization-loop -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-bifang-amazon-keyword-optimization-loop --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/bifang/sealeap-bifang-amazon-keyword-optimization-loop .agents/skills/sealeap-bifang-amazon-keyword-optimization-loop && 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-bifang-amazon-keyword-optimization-loop" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/bifang/sealeap-bifang-amazon-keyword-optimization-loop into .agents/skills/sealeap-bifang-amazon-keyword-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-bifang-amazon-keyword-optimization-loop", 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-bifang-amazon-keyword-optimization-loop -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-bifang-amazon-keyword-optimization-loop --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/bifang/sealeap-bifang-amazon-keyword-optimization-loop .cursor/skills/sealeap-bifang-amazon-keyword-optimization-loop && 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-bifang-amazon-keyword-optimization-loop" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/bifang/sealeap-bifang-amazon-keyword-optimization-loop into .cursor/skills/sealeap-bifang-amazon-keyword-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-bifang-amazon-keyword-optimization-loop", 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/bifang/sealeap-bifang-amazon-keyword-optimization-loop--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-bifang-amazon-keyword-optimization-loop -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-bifang-amazon-keyword-optimization-loop --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/bifang/sealeap-bifang-amazon-keyword-optimization-loop .gemini/skills/sealeap-bifang-amazon-keyword-optimization-loop && 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-bifang-amazon-keyword-optimization-loop" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/bifang/sealeap-bifang-amazon-keyword-optimization-loop into .gemini/skills/sealeap-bifang-amazon-keyword-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-bifang-amazon-keyword-optimization-loop", 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-bifang-amazon-keyword-optimization-loopInstalls 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-bifang-amazon-keyword-optimization-loop -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/bifang/sealeap-bifang-amazon-keyword-optimization-loop .github/skills/sealeap-bifang-amazon-keyword-optimization-loop && 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-bifang-amazon-keyword-optimization-loop" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/bifang/sealeap-bifang-amazon-keyword-optimization-loop into .github/skills/sealeap-bifang-amazon-keyword-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-bifang-amazon-keyword-optimization-loop", 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-bifang-amazon-keyword-optimization-loop -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-bifang-amazon-keyword-optimization-loop --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/bifang/sealeap-bifang-amazon-keyword-optimization-loop .opencode/skills/sealeap-bifang-amazon-keyword-optimization-loop && 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-bifang-amazon-keyword-optimization-loop" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/bifang/sealeap-bifang-amazon-keyword-optimization-loop into .opencode/skills/sealeap-bifang-amazon-keyword-optimization-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-bifang-amazon-keyword-optimization-loop", 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-bifang-amazon-keyword-optimization-loop- GitHub stars
- 251
- Token cost
- ~849 tokens
- SKILL.md length
- 174 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Run a five-stage keyword workflow for an Amazon listing: collect candidate terms from several comparable ASINs, screen them by product-fact relevance and observed performance, embed the shortlist…
- 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。 → …
- 关键词怎么找、关键词筛选、标题埋词、关键词清单、关键词加权、关键词监控调整
- 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 Bifang Amazon Keyword Optimization Loop is an agent skill from xjli360/sealeap-amazon-skills. Run a five-stage keyword workflow for an Amazon listing: collect candidate terms from several comparable ASINs, screen them by product-fact relevance and observed performance, embed the shortlist into listing copy, raise weight on a few priority terms through controlled advertising, then monitor indexing and rank to decide what to add, cut or roll back. Use for 关键词怎么找、关键词筛选、标题埋词、关键词清单、关键词加权、关键词监控调整. Do not use to rewrite a live listing or change bids without an approved change table and a rank baseline.
Its SKILL.md is about 850 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 Writing & Content, covering Copywriting. 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
- 关键词怎么找、关键词筛选、标题埋词、关键词清单、关键词加权、关键词监控调整
- Rewrite a live listing
- Change bids without an approved change table and a rank baseline
Example prompts
- “/sealeap-bifang-amazon-keyword-optimization-loop”
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 Bifang Amazon Keyword Optimization Loop loads about 849 tokens when it runs, and up to ~3.5k if it reads all its reference files. Until then it costs about 139 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, ~849 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-bifang-amazon-keyword-optimization-loop/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- sealeap-bifang-amazon-keyword-optimization-loop
- description
- Run a five-stage keyword workflow for an Amazon listing: collect candidate terms from several comparable ASINs, screen them by product-fact relevance and observed performance, embed the shortlist into listing copy, raise weight on a few priority terms through controlled advertising, then monitor indexing and rank to decide what to add, cut or roll back. Use for 关键词怎么找、关键词筛选、标题埋词、关键词清单、关键词加权、关键词监控调整. Do not use to rewrite a live listing or change bids without an approved change table and a rank baseline.
Amazon 关键词搜集筛选埋词闭环
目标
Run a five-stage keyword workflow for an Amazon listing: collect candidate terms from several comparable ASINs, screen them by product-fact relevance and observed performance, embed the shortlist into listing copy, raise weight on a few priority terms through controlled advertising, then monitor indexing and rank to decide what to add, cut or roll back.
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。
- 来源建议的竞品样本数量是经验值；以候选词能否形成多样本交叉为准，不作为规律。
- “他人品牌词无转化”和“核心大词中小卖家打不起”是来源经验，需以当前账户的搜索词报告与 CPC 校准；品牌词还涉及商标与广告政策，按当前政策处理。
- “官方社媒促销码比站外促销更能拉升关键词权重”是来源主观感受，属待验证假设；只能通过账户内前后对比观测，不外推为平台算法。
- 关键词收录与排名查询受地区、登录态、变体与个性化影响；单次查询不作结论，需同一条件多次采样。
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：
- 先固定对象：marketplace、ASIN/SKU、产品事实（核心功能、规格、适配范围）与目标购买意图；再选取若干个同购买意图、表现稳定的可比 ASIN 作为反查样本，样本数量以候选词能形成多样本交叉为准，只依赖单一 ASIN 的词表视为样本不足并标 NEEDS_EVIDENCE。
- 搜集：用关键词反查（优先带转化记录的出单词反查）与关键词拓展拉取各样本词表，合并去重后保留每个词的来源 ASIN 数、搜索量代理、点击/转化份额等原始字段形成候选词池；这一步只收集不取舍。
- 筛选（最耗时的一步）：逐词按三类判断——①与本品事实的匹配度：产品名称级主词必须进标题，他人品牌词一律剔除，含主观最高级或依赖外部条件才成立的宣称词只有在产品事实能长期支撑时才保留；②多样本交叉出现次数；③观测指标（点击/转化份额、垄断度）。用对比视图把相近词放在一起看，再分组为标题必入词、五点/描述补充词、广告候选词，并写下每个剔除词的理由。
- 埋词：把分组清单交给撰写者（母语撰写者或自己），要求覆盖清单内全部指定词且语句通顺地道；交付后逐词核对覆盖情况，缺词回炉；改动前保存旧版文案作为回退值。
- 加权：只对少数优先长尾词用手动精准投放拉动；核心大词是否投放按当前账户的 CPC 与盈亏平衡 ACOS 校准而不是默认投放；已完成品牌备案的卖家可评估平台官方的社媒促销码等工具；每次加权动作写入变更记录（对象、旧值、新值、预期）。
- 监控：改动后在固定采样条件下查关键词收录与自然/广告位置，与埋词前基线比较；目标词持续下滑或收录消失时先回退文案再排查；按周期用数据决定加词、否词与预算/竞价调整，结论只写成账户内证据，不外推为平台规律。
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：获取可比 ASIN 的关键词反查、搜索量与相关词代理数据。
- 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
- 候选词池（含来源 ASIN 数与观测指标字段）
- 分组关键词清单（标题必入/补充/广告候选，含剔除理由）
- 埋词覆盖核对表与旧版文案回退值
- 加权动作变更记录
- 关键词收录与位置监控基线及复盘结论
- 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/bifang/sealeap-bifang-amazon-keyword-optimization-loop 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 Bifang Amazon Keyword Optimization Loop 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 Bifang Amazon Keyword Optimization Loop this skillxjli360/sealeap-amazon-skills | 251 | — | ~849 | Automated safety check: Pass | MIT | |
| Asd Ste100danyuchn/asd-ste100-skill | 4.3k | — | ~4.1k | Automated safety check: Pass | MIT | |
| AI Copywritermikiarlo3/ai-copywriter | 1.2k | — | ~12k | Automated safety check: Pass | MIT | |
| Brand Voice Guideluongnv89/claude-howto | 42k | — | ~609 | Automated safety check: Pass | MIT | |
| Ralph Copywritermuratcankoylan/ralph-wiggum-marketer | 778 | — | ~2.4k | Automated safety check: Pass | None | |
| Humanities Writing Companiontizzy916/humanities-writing-companion | 436 | — | ~3.4k | Automated safety check: Pass | CC-BY-NC-4.0 |
Similar skills
AI Copywriter
mikiarlo3/ai-copywriter
Write copy that converts and doesn't sound like a robot. An agent skill from mikiarlo3/ai-copywriter.
Brand Voice Guide
luongnv89/claude-howto
Ensure all communication matches brand voice and tone guidelines. Use when creating marketing copy, customer communications, public-facing content, or when…
Ralph Copywriter
muratcankoylan/ralph-wiggum-marketer
A skill your agent uses when the user asks to "analyze my content", "learn my writing style", "research competitors", "find content angles", "improve my blog", "write like me", "embody my brand…
Humanities Writing Companion
tizzy916/humanities-writing-companion
Help with humanities scholarly writing: sharpen research questions, map supplied readings, plan and draft arguments, review chapters, preserve authorial voice, and respond to reviewers.
Xiaoma Durex Copywriter
crawfordxx/xiaoma-durex-copywriter
用杜蕾斯黄金期（2011-2017 环时互动）那套「双层语义 + 留白」的方法产出文案与海报。先识别用户意图并给 3-5 个方案供选，再出短文案（长文案可选）+ 五种比例配图。适用于借势热点、节日节气、产品卖点、课程/知识付费推广、自媒体标题与封面、品牌人格化运营。当用户说「写个文案」「借势热点」「节日海报」「想句…
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
Categories
Questions about Sealeap Bifang Amazon Keyword Optimization Loop
What does Sealeap Bifang Amazon Keyword Optimization Loop do?
Run a five-stage keyword workflow for an Amazon listing: collect candidate terms from several comparable ASINs, screen them by product-fact relevance and observed performance, embed the shortlist…. Sealeap Bifang Amazon Keyword Optimization Loop is an agent skill from xjli360/sealeap-amazon-skills. Run a five-stage keyword workflow for an Amazon listing: collect candidate terms from several comparable ASINs, screen them by product-fact relevance and observed performance, embed the shortlist into listing copy, raise weight on a few priority terms through controlled advertising, then monitor indexing and rank to decide what to add, cut or roll back.
When should I use Sealeap Bifang Amazon Keyword Optimization Loop?
Sealeap Bifang Amazon Keyword Optimization Loop fits situations like: 关键词怎么找、关键词筛选、标题埋词、关键词清单、关键词加权、关键词监控调整; rewrite a live listing; change bids without an approved change table and a rank baseline.
How do I install Sealeap Bifang Amazon Keyword Optimization Loop in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-bifang-amazon-keyword-optimization-loop -a claude-code`. Or copy the skill folder (amazon-skills/bilibili/bifang/sealeap-bifang-amazon-keyword-optimization-loop in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-bifang-amazon-keyword-optimization-loop in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Bifang Amazon Keyword Optimization Loop in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-bifang-amazon-keyword-optimization-loop -a codex`. Or copy the skill folder (amazon-skills/bilibili/bifang/sealeap-bifang-amazon-keyword-optimization-loop in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-bifang-amazon-keyword-optimization-loop in your project. Codex loads it when a task matches its description.
Can I use Sealeap Bifang Amazon Keyword Optimization Loop 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-bifang-amazon-keyword-optimization-loop -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-bifang-amazon-keyword-optimization-loop, .gemini/skills/sealeap-bifang-amazon-keyword-optimization-loop, .github/skills/sealeap-bifang-amazon-keyword-optimization-loop and .opencode/skills/sealeap-bifang-amazon-keyword-optimization-loop in your project.
What does Sealeap Bifang Amazon Keyword Optimization Loop need to run?
Going by SKILL.md and its folder, Sealeap Bifang Amazon Keyword Optimization Loop needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Bifang Amazon Keyword Optimization Loop 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 Bifang Amazon Keyword Optimization Loop 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 Bifang Amazon Keyword Optimization Loop use?
Sealeap Bifang Amazon Keyword Optimization Loop 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 Bifang Amazon Keyword Optimization Loop use?
About 849 tokens (SKILL.md is roughly 3.4k 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 Bifang Amazon Keyword Optimization Loop?
Skills that share tags, products or a category with Sealeap Bifang Amazon Keyword Optimization Loop: Asd Ste100 (danyuchn/asd-ste100-skill, 4.3k stars), AI Copywriter (mikiarlo3/ai-copywriter, 1.2k stars), Brand Voice Guide (luongnv89/claude-howto, 42k stars) and Ralph Copywriter (muratcankoylan/ralph-wiggum-marketer, 778 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sealeap Bifang Amazon Keyword Optimization Loop?
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.