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 Xiezhi Amazon Conversion Rate Prelaunch Estimation
Estimate a defensible pre-launch conversion range from Amazon first-party opportunity data, competitor traffic proxies, and unit economics.
Install Sealeap Xiezhi Amazon Conversion Rate Prelaunch Estimation
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation --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/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation .claude/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation && 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-xiezhi-amazon-conversion-rate-prelaunch-estimation" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation into .claude/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation", 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/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimationType 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-xiezhi-amazon-conversion-rate-prelaunch-estimation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation --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/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation .agents/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation && 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-xiezhi-amazon-conversion-rate-prelaunch-estimation" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation into .agents/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation", 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-xiezhi-amazon-conversion-rate-prelaunch-estimation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation --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/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation .cursor/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation && 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-xiezhi-amazon-conversion-rate-prelaunch-estimation" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation into .cursor/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation", 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/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation--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-xiezhi-amazon-conversion-rate-prelaunch-estimation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation --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/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation .gemini/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation && 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-xiezhi-amazon-conversion-rate-prelaunch-estimation" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation into .gemini/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation", 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-xiezhi-amazon-conversion-rate-prelaunch-estimationInstalls 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-xiezhi-amazon-conversion-rate-prelaunch-estimation -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/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation .github/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation && 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-xiezhi-amazon-conversion-rate-prelaunch-estimation" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation into .github/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation", 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-xiezhi-amazon-conversion-rate-prelaunch-estimation -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-xiezhi-amazon-conversion-rate-prelaunch-estimation --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/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation .opencode/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation && 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-xiezhi-amazon-conversion-rate-prelaunch-estimation" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation into .opencode/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation", 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-xiezhi-amazon-conversion-rate-prelaunch-estimation- GitHub stars
- 251
- Token cost
- ~552 tokens
- SKILL.md length
- 126 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Estimate a defensible pre-launch conversion range from Amazon first-party opportunity data, competitor traffic proxies, and unit economics.
- Works in 5 steps: 统一单位经济 → 估单品 CVR → 估市场 CVR → …
- A product appears profitable only under an assumed CVR and the team needs a risk-aware launch gate
- SKILL.md covers 目标, 适用任务, 开始前要拿到 and 不可妥协的边界, plus 4 more sections
- Runs Python scripts from its folder
What it does
Sealeap Xiezhi Amazon Conversion Rate Prelaunch Estimation is an agent skill from xjli360/sealeap-amazon-skills. Estimate a defensible pre-launch conversion range from Amazon first-party opportunity data, competitor traffic proxies, and unit economics. Use when a product appears profitable only under an assumed CVR and the team needs a risk-aware launch gate.
Its SKILL.md is about 550 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 Conversion rate optimization and Financial modeling. 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
- A product appears profitable only under an assumed CVR and the team needs a risk-aware launch gate
- Tasks that involve Conversion rate optimization
- Tasks that involve Financial modeling
Example prompts
- “/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation”
Requirements
- Python 3
Workflow steps
5 steps, taken from the step headings in SKILL.md.
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 Xiezhi Amazon Conversion Rate Prelaunch Estimation loads about 552 tokens when it runs, and up to ~3k if it reads all its reference files. Until then it costs about 77 tokens; SKILL.md has 126 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). 126 words, ~552 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation
- description
- Estimate a defensible pre-launch conversion range from Amazon first-party opportunity data, competitor traffic proxies, and unit economics. Use when a product appears profitable only under an assumed CVR and the team needs a risk-aware launch gate.
Amazon 上市前转化率估算
目标
用头部链接和细分市场两种口径交叉估算转化率，再判断保本 CVR 是否现实。
适用任务
- 测算候选产品的保本转化率。
- 用单 ASIN 与市场整体数据交叉验证。
- 识别长决策、低转化且广告难盈利的市场。
开始前要拿到
- 售价、落地成本、Amazon 费用、优惠和目标利润。
- 精准词 CPC 区间。
- 竞品销量与搜索点击代理数据。
- Amazon 商机探测器或其他一方市场购买率数据。
缺少字段时列出证据缺口，并把相关结论标为 FACT、ESTIMATE、ASSUMPTION 或 UNKNOWN；不要补造数据。
不可妥协的边界
- 第三方数据均为估算或代理证据；Amazon 一方报告、后台实时字段和产品事实优先。
- 经验阈值只能作为可调起点，必须展示敏感性分析，不能写成 Amazon 官方规则。
- 不得捏造销量、搜索量、CPC、CVR、成本、认证、产品属性或消费者需求。
- 默认提供诊断或草案。写入前展示对象、旧值、新值、影响、停止线与回退，核对用户已有授权是否覆盖对象、动作与预算；范围已明确授权时继续执行并回读核验，只有未覆盖或扩大的范围才请求批准。
- 不输出或保存素材来源身份、账号、链接、作品编号、互动数据、原始话术或其他可反查来源的线索。
- 不得把销量估算与点击估算的比值写成真实转化率。
- 当前 Amazon 一方字段定义优先于任何历史方法。
工作流
1. 统一单位经济
计算广告前贡献毛利、盈亏平衡 CPA、ACoS 和所需 CVR，并明确税费、退款和优惠口径。
2. 估单品 CVR
只有订单与点击来自相同流量范围、对象、时间窗和归因口径时才估算订单 CVR。全渠道销量除以搜索点击只能标为需求比例代理，不能作为 CVR 或直接代入 CPA；缺少可比样本时用明确标注的假设区间并保留 HOLD。
3. 估市场 CVR
读取细分市场购买率、转化购买率或等价一方指标，解释访客、点击、归因窗差异。
4. 形成区间
不机械取单点，使用保守/基准/乐观三档并剔除口径不可比样本。
5. 做立项闸门
若头部或市场基准仍低于保本 CVR，则 HOLD；只有差异化能被证据支持时才建立例外情景。
判断标准
- CPA = CPC / 订单 CVR；保本订单 CVR = CPC / 广告前每单贡献毛利。贡献毛利非正、分母为零或所需 CVR 超过 100% 时，标为当前经济模型不可行。
- 搜索点击口径通常不能代表全部流量，单 ASIN 结果必须标注偏差方向。
- 购买率与转化购买率定义可能随报表变化，必须记录当前官方字段说明。
- 头部转化差时，新品默认不能假设显著优于头部。
第三方 MCP 数据
需要外部关键词、竞品、评论或公开网页证据时，读取 references/mcp-data-plan.md，并使用 scripts/mcp_research.py。
- 先动态执行
tools/list、search-tools和describe，依据实时inputSchema构造参数。 - 凭证只从环境变量读取，不进入参数、URL、Skill、终端输出或 Git。
- 可能计费的
tools/call先展示 Provider、工具、无密钥参数、预计成本与输出位置，核对已有授权；仅在授权覆盖本次范围时使用--allow-cost，该标志不是费用上限。 - 脱敏结果用
--output写入 Skill 包之外的任务私有目录；不假设安装位置受仓库.gitignore保护。第三方数据标为估算或代理证据。 - 失败一次后记录缺口，不以重复付费重试掩盖不可用状态。
必须交付的结果
- 单位经济表
- 单 ASIN CVR 区间
- 市场 CVR 区间
- 保本敏感性矩阵
- GO/HOLD/NO-GO 及证据缺口
结尾列出站点、数据窗口、证据来源、关键假设、缺口、风险、下一步和所有待批准动作。证据不足时写 HOLD，不得包装成可直接执行。
执行细节、证据字段和质量检查见 references/playbook.md。
© 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/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation 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 Xiezhi Amazon Conversion Rate Prelaunch Estimation 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 Xiezhi Amazon Conversion Rate Prelaunch Estimation this skillxjli360/sealeap-amazon-skills | 251 | — | ~552 | Automated safety check: Pass | MIT | |
| Creating Financial ModelsChen-zexi/open-ptc-agent | 729 | 3 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Dcf ModelWind-Alice/AliceMarket | 134 | 2 repos | ~12k | Automated safety check: Pass | None | |
| Analyst EstimatesOctagonAI/skills | 127 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Historical Financial RatingsOctagonAI/skills | 127 | — | ~1k | Automated safety check: Pass | MIT | |
| Ratings SnapshotOctagonAI/skills | 127 | — | ~1.1k | Automated safety check: Pass | MIT |
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Questions about Sealeap Xiezhi Amazon Conversion Rate Prelaunch Estimation
What does Sealeap Xiezhi Amazon Conversion Rate Prelaunch Estimation do?
Estimate a defensible pre-launch conversion range from Amazon first-party opportunity data, competitor traffic proxies, and unit economics. Sealeap Xiezhi Amazon Conversion Rate Prelaunch Estimation is an agent skill from xjli360/sealeap-amazon-skills. Estimate a defensible pre-launch conversion range from Amazon first-party opportunity data, competitor traffic proxies, and unit economics.
When should I use Sealeap Xiezhi Amazon Conversion Rate Prelaunch Estimation?
Sealeap Xiezhi Amazon Conversion Rate Prelaunch Estimation fits situations like: A product appears profitable only under an assumed CVR and the team needs a risk-aware launch gate; tasks that involve Conversion rate optimization; tasks that involve Financial modeling.
How do I install Sealeap Xiezhi Amazon Conversion Rate Prelaunch Estimation in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation -a claude-code`. Or copy the skill folder (amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Xiezhi Amazon Conversion Rate Prelaunch Estimation in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation -a codex`. Or copy the skill folder (amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation in your project. Codex loads it when a task matches its description.
Can I use Sealeap Xiezhi Amazon Conversion Rate Prelaunch Estimation 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-xiezhi-amazon-conversion-rate-prelaunch-estimation -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-xiezhi-amazon-conversion-rate-prelaunch-estimation, .gemini/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation, .github/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation and .opencode/skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation in your project.
What does Sealeap Xiezhi Amazon Conversion Rate Prelaunch Estimation need to run?
Going by SKILL.md and its folder, Sealeap Xiezhi Amazon Conversion Rate Prelaunch Estimation needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Xiezhi Amazon Conversion Rate Prelaunch Estimation 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 Xiezhi Amazon Conversion Rate Prelaunch Estimation 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 Xiezhi Amazon Conversion Rate Prelaunch Estimation use?
Sealeap Xiezhi Amazon Conversion Rate Prelaunch Estimation 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 Xiezhi Amazon Conversion Rate Prelaunch Estimation use?
About 552 tokens (SKILL.md is roughly 2.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.4k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Xiezhi Amazon Conversion Rate Prelaunch Estimation?
Skills that share tags, products or a category with Sealeap Xiezhi Amazon Conversion Rate Prelaunch Estimation: Creating Financial Models (Chen-zexi/open-ptc-agent, 729 stars), Dcf Model (Wind-Alice/AliceMarket, 134 stars), Analyst Estimates (OctagonAI/skills, 127 stars) and Historical Financial Ratings (OctagonAI/skills, 127 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sealeap Xiezhi Amazon Conversion Rate Prelaunch Estimation?
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.