Creating Financial Models
Chen-zexi/open-ptc-agent
This skill provides an advanced financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning for investment decisions
Agent skill
Sealeap Taotie Amazon Keyword Driven Niche Product Screening
Screen product candidates starting from a seed keyword: read search-trend shape, competitor launch age and growth speed, review count and rating, then segment by attribute, audience and use case…
Install Sealeap Taotie Amazon Keyword Driven Niche Product Screening
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-taotie-amazon-keyword-driven-niche-product-screening -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-taotie-amazon-keyword-driven-niche-product-screening --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/taotie/sealeap-taotie-amazon-keyword-driven-niche-product-screening .claude/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening && 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-taotie-amazon-keyword-driven-niche-product-screening" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/taotie/sealeap-taotie-amazon-keyword-driven-niche-product-screening into .claude/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-taotie-amazon-keyword-driven-niche-product-screening", 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/taotie/sealeap-taotie-amazon-keyword-driven-niche-product-screeningType 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-taotie-amazon-keyword-driven-niche-product-screening -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-taotie-amazon-keyword-driven-niche-product-screening --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/taotie/sealeap-taotie-amazon-keyword-driven-niche-product-screening .agents/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening && 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-taotie-amazon-keyword-driven-niche-product-screening" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/taotie/sealeap-taotie-amazon-keyword-driven-niche-product-screening into .agents/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-taotie-amazon-keyword-driven-niche-product-screening", 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-taotie-amazon-keyword-driven-niche-product-screening -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-taotie-amazon-keyword-driven-niche-product-screening --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/taotie/sealeap-taotie-amazon-keyword-driven-niche-product-screening .cursor/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening && 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-taotie-amazon-keyword-driven-niche-product-screening" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/taotie/sealeap-taotie-amazon-keyword-driven-niche-product-screening into .cursor/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-taotie-amazon-keyword-driven-niche-product-screening", 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/taotie/sealeap-taotie-amazon-keyword-driven-niche-product-screening--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-taotie-amazon-keyword-driven-niche-product-screening -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-taotie-amazon-keyword-driven-niche-product-screening --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/taotie/sealeap-taotie-amazon-keyword-driven-niche-product-screening .gemini/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening && 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-taotie-amazon-keyword-driven-niche-product-screening" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/taotie/sealeap-taotie-amazon-keyword-driven-niche-product-screening into .gemini/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-taotie-amazon-keyword-driven-niche-product-screening", 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-taotie-amazon-keyword-driven-niche-product-screeningInstalls 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-taotie-amazon-keyword-driven-niche-product-screening -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/taotie/sealeap-taotie-amazon-keyword-driven-niche-product-screening .github/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening && 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-taotie-amazon-keyword-driven-niche-product-screening" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/taotie/sealeap-taotie-amazon-keyword-driven-niche-product-screening into .github/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-taotie-amazon-keyword-driven-niche-product-screening", 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-taotie-amazon-keyword-driven-niche-product-screening -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-taotie-amazon-keyword-driven-niche-product-screening --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/taotie/sealeap-taotie-amazon-keyword-driven-niche-product-screening .opencode/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening && 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-taotie-amazon-keyword-driven-niche-product-screening" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/bilibili/taotie/sealeap-taotie-amazon-keyword-driven-niche-product-screening into .opencode/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-taotie-amazon-keyword-driven-niche-product-screening", 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-taotie-amazon-keyword-driven-niche-product-screening- GitHub stars
- 251
- Token cost
- ~830 tokens
- SKILL.md length
- 160 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Screen product candidates starting from a seed keyword: read search-trend shape, competitor launch age and growth speed, review count and rating, then segment by attribute, audience and use case…
- 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。 → …
- 新手怎么选品、关键词选品、细分市场怎么找、看趋势图怎么判断、上架时间和增长速度、供需比怎么用、历史价格怎么看、选品表怎么设计
- 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 Taotie Amazon Keyword Driven Niche Product Screening is an agent skill from xjli360/sealeap-amazon-skills. Screen product candidates starting from a seed keyword: read search-trend shape, competitor launch age and growth speed, review count and rating, then segment by attribute, audience and use case using variation and high-frequency-word signals, check historical price ranges and listing-count supply ratios, and log each candidate into a comparable selection table. Use for 新手怎么选品、关键词选品、细分市场怎么找、看趋势图怎么判断、上架时间和增长速度、供需比怎么用、历史价格怎么看、选品表怎么设计. Do not use to output a GO decision without the unit-economics check or compliance…
Its SKILL.md is about 830 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 Business, Finance & HR, covering Financial modeling. 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
- 新手怎么选品、关键词选品、细分市场怎么找、看趋势图怎么判断、上架时间和增长速度、供需比怎么用、历史价格怎么看、选品表怎么设计
- Output a GO decision without the unit-economics check
- Compliance and IP screening
Example prompts
- “/sealeap-taotie-amazon-keyword-driven-niche-product-screening”
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 Taotie Amazon Keyword Driven Niche Product Screening loads about 830 tokens when it runs, and up to ~3.4k if it reads all its reference files. Until then it costs about 149 tokens; SKILL.md has 160 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). 160 words, ~830 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- sealeap-taotie-amazon-keyword-driven-niche-product-screening
- description
- Screen product candidates starting from a seed keyword: read search-trend shape, competitor launch age and growth speed, review count and rating, then segment by attribute, audience and use case using variation and high-frequency-word signals, check historical price ranges and listing-count supply ratios, and log each candidate into a comparable selection table. Use for 新手怎么选品、关键词选品、细分市场怎么找、看趋势图怎么判断、上架时间和增长速度、供需比怎么用、历史价格怎么看、选品表怎么设计. Do not use to output a GO decision without the unit-economics check or compliance and IP screening.
Amazon 关键词驱动的细分市场选品筛选
目标
Screen product candidates starting from a seed keyword: read search-trend shape, competitor launch age and growth speed, review count and rating, then segment by attribute, audience and use case using variation and high-frequency-word signals, check historical price ranges and listing-count supply ratios, and log each candidate into a comparable selection table.
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。
- 「半年内上架并快速增长的品新手都有机会」「越早发现成功率越高」是来源经验判断，需用本类目近一年新品的存活与增长数据校准。
- 商品数/供需比、增长率、评论数等数字都是第三方估算，标为 ESTIMATE；不同工具口径差异大，不得写成事实，也不得设固定阈值。
- 来源举例的具体品类、价格与销量不转译；工具推广与分销邀约等内容不采纳。
- 变体异常高价可能是断货或临时策略，「高价空缺 = 机会」只是待验证假设，需看同行与历史价格。
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、类目、价格带、上架时间与运营模式
- 候选品与同购买意图可比样本的销量、评论、价格和上架时间
- 关键词需求、历史趋势、广告依赖、同款密度和品牌集中度
- 采购、头程、平台费、退货、仓储、交期和合规/IP 基础信息
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：
- 确定一个种子关键词（可来自自己能深耕的类目或商标类别），在关键词/选品工具类别中过滤搜索结果；新手先不叠加复杂筛选条件，先看结果列表的整体形态。
- 看搜索趋势形状：优先「前段平、近期明显抬升且持续」的词，标注抬升起点；对型号词或节日词识别其生命周期（新型号上市替代旧型号、季节回落），并写下需求增长的背后原因（新用户群扩大、新功能、社媒使用场景等）作为待验证假设。
- 看竞品的上架时间与增长速度：找上架不久却已进入类目前列、评论数尚少的 Listing，作为「新品能进入」的证据；越早发现这类信号越有利，因此要按固定周期重复抓取。
- 做细分：从变体（颜色/尺寸/型号适配）与高频词（迷你、带支架、材质等）拆出属性、人群、用途三个维度，找出有搜索需求但现有热销品没覆盖的组合；变体中长期异常高价的款式可能是空缺信号，需与同行对比确认。
- 读供需与价格：搜索结果商品数只作竞争难度的粗指标，重点看头部十几个 Listing 的价格带、评论、上架时长；售价用价格历史工具看区间而非当下促销价，市场均价按头部主流价格带取值，不必对所有竞品做精确平均。
- 把每个候选写入选品表：核心词、场景词、长尾词、趋势判断、竞品链接与截图、优缺点（来自评论）、采购成本、目标售价；同一需求下列出不同价位的产品解决方案，对比后再进入单位经济测算。
- 评分低但需求增长的品不直接跟做，沿其需求方向寻找评分更好或价位更高的替代方案；候选表达到三个以上再做下一步测算与打样。
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：获取关键词搜索趋势、高频词、竞品上架时间与销量估算、历史价格区间的第三方代理证据。
- 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
- 种子关键词与趋势判读记录
- 竞品上架时间与增长对照表
- 属性/人群/用途细分矩阵
- 价格带与供需观察表
- 候选选品表
- 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/bilibili/taotie/sealeap-taotie-amazon-keyword-driven-niche-product-screening 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 Taotie Amazon Keyword Driven Niche Product Screening 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 Taotie Amazon Keyword Driven Niche Product Screening this skillxjli360/sealeap-amazon-skills | 251 | — | ~830 | Automated safety check: Pass | MIT | |
| Creating Financial ModelsChen-zexi/open-ptc-agent | 729 | 3 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Equity ResearchrollingSirius/equity-research-skill | 453 | — | ~1.5k | Automated safety check: Pass | MIT | |
| SaaS Metrics Coachrongxinzy/RongxinAI | 154 | 2 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Startup Financial Modelingnicepkg/auto-company | 195 | 11 repos | ~2.8k | Automated safety check: Pass | None | |
| Stock Value AnalyzerFunnyKun/stock-value-analyzer | 141 | — | ~3.3k | Automated safety check: Pass | None |
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Questions about Sealeap Taotie Amazon Keyword Driven Niche Product Screening
What does Sealeap Taotie Amazon Keyword Driven Niche Product Screening do?
Screen product candidates starting from a seed keyword: read search-trend shape, competitor launch age and growth speed, review count and rating, then segment by attribute, audience and use case…. Sealeap Taotie Amazon Keyword Driven Niche Product Screening is an agent skill from xjli360/sealeap-amazon-skills. Screen product candidates starting from a seed keyword: read search-trend shape, competitor launch age and growth speed, review count and rating, then segment by attribute, audience and use case using variation and high-frequency-word signals, check historical price ranges and listing-count supply ratios, and log each candidate into a comparable selection table.
When should I use Sealeap Taotie Amazon Keyword Driven Niche Product Screening?
Sealeap Taotie Amazon Keyword Driven Niche Product Screening fits situations like: 新手怎么选品、关键词选品、细分市场怎么找、看趋势图怎么判断、上架时间和增长速度、供需比怎么用、历史价格怎么看、选品表怎么设计; output a GO decision without the unit-economics check; compliance and IP screening.
How do I install Sealeap Taotie Amazon Keyword Driven Niche Product Screening in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-taotie-amazon-keyword-driven-niche-product-screening -a claude-code`. Or copy the skill folder (amazon-skills/bilibili/taotie/sealeap-taotie-amazon-keyword-driven-niche-product-screening in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Taotie Amazon Keyword Driven Niche Product Screening in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-taotie-amazon-keyword-driven-niche-product-screening -a codex`. Or copy the skill folder (amazon-skills/bilibili/taotie/sealeap-taotie-amazon-keyword-driven-niche-product-screening in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening in your project. Codex loads it when a task matches its description.
Can I use Sealeap Taotie Amazon Keyword Driven Niche Product Screening 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-taotie-amazon-keyword-driven-niche-product-screening -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-taotie-amazon-keyword-driven-niche-product-screening, .gemini/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening, .github/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening and .opencode/skills/sealeap-taotie-amazon-keyword-driven-niche-product-screening in your project.
What does Sealeap Taotie Amazon Keyword Driven Niche Product Screening need to run?
Going by SKILL.md and its folder, Sealeap Taotie Amazon Keyword Driven Niche Product Screening needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Taotie Amazon Keyword Driven Niche Product Screening 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 Taotie Amazon Keyword Driven Niche Product Screening 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 Taotie Amazon Keyword Driven Niche Product Screening use?
Sealeap Taotie Amazon Keyword Driven Niche Product Screening 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 Taotie Amazon Keyword Driven Niche Product Screening use?
About 830 tokens (SKILL.md is roughly 3.3k 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 2.6k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Taotie Amazon Keyword Driven Niche Product Screening?
Skills that share tags, products or a category with Sealeap Taotie Amazon Keyword Driven Niche Product Screening: Creating Financial Models (Chen-zexi/open-ptc-agent, 729 stars), Equity Research (rollingSirius/equity-research-skill, 453 stars), SaaS Metrics Coach (rongxinzy/RongxinAI, 154 stars) and Startup Financial Modeling (nicepkg/auto-company, 195 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sealeap Taotie Amazon Keyword Driven Niche Product Screening?
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.