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n1m21n/Infinite
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Agent skill
Sealeap Bixie Amazon Unmet Demand Keyword To Product
Identify keywords with rising search volume and click interest but below-benchmark conversion as unmet-demand signals, then run them through AI-assisted product-candidate generation and a market…
Install Sealeap Bixie Amazon Unmet Demand Keyword To Product
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-bixie-amazon-unmet-demand-keyword-to-product -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-bixie-amazon-unmet-demand-keyword-to-product --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/weixin/bixie/sealeap-bixie-amazon-unmet-demand-keyword-to-product .claude/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product && 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-bixie-amazon-unmet-demand-keyword-to-product" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/weixin/bixie/sealeap-bixie-amazon-unmet-demand-keyword-to-product into .claude/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-bixie-amazon-unmet-demand-keyword-to-product", 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/weixin/bixie/sealeap-bixie-amazon-unmet-demand-keyword-to-productType 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-bixie-amazon-unmet-demand-keyword-to-product -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-bixie-amazon-unmet-demand-keyword-to-product --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/weixin/bixie/sealeap-bixie-amazon-unmet-demand-keyword-to-product .agents/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product && 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-bixie-amazon-unmet-demand-keyword-to-product" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/weixin/bixie/sealeap-bixie-amazon-unmet-demand-keyword-to-product into .agents/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-bixie-amazon-unmet-demand-keyword-to-product", 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-bixie-amazon-unmet-demand-keyword-to-product -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-bixie-amazon-unmet-demand-keyword-to-product --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/weixin/bixie/sealeap-bixie-amazon-unmet-demand-keyword-to-product .cursor/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product && 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-bixie-amazon-unmet-demand-keyword-to-product" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/weixin/bixie/sealeap-bixie-amazon-unmet-demand-keyword-to-product into .cursor/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-bixie-amazon-unmet-demand-keyword-to-product", 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/weixin/bixie/sealeap-bixie-amazon-unmet-demand-keyword-to-product--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-bixie-amazon-unmet-demand-keyword-to-product -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-bixie-amazon-unmet-demand-keyword-to-product --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/weixin/bixie/sealeap-bixie-amazon-unmet-demand-keyword-to-product .gemini/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product && 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-bixie-amazon-unmet-demand-keyword-to-product" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/weixin/bixie/sealeap-bixie-amazon-unmet-demand-keyword-to-product into .gemini/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-bixie-amazon-unmet-demand-keyword-to-product", 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-bixie-amazon-unmet-demand-keyword-to-productInstalls 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-bixie-amazon-unmet-demand-keyword-to-product -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/weixin/bixie/sealeap-bixie-amazon-unmet-demand-keyword-to-product .github/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product && 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-bixie-amazon-unmet-demand-keyword-to-product" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/weixin/bixie/sealeap-bixie-amazon-unmet-demand-keyword-to-product into .github/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-bixie-amazon-unmet-demand-keyword-to-product", 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-bixie-amazon-unmet-demand-keyword-to-product -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-bixie-amazon-unmet-demand-keyword-to-product --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/weixin/bixie/sealeap-bixie-amazon-unmet-demand-keyword-to-product .opencode/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product && 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-bixie-amazon-unmet-demand-keyword-to-product" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/weixin/bixie/sealeap-bixie-amazon-unmet-demand-keyword-to-product into .opencode/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-bixie-amazon-unmet-demand-keyword-to-product", 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-bixie-amazon-unmet-demand-keyword-to-product- GitHub stars
- 251
- Token cost
- ~706 tokens
- SKILL.md length
- 147 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Identify keywords with rising search volume and click interest but below-benchmark conversion as unmet-demand signals, then run them through AI-assisted product-candidate generation and a market…
- 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。 → …
- 找搜索量高转化低的词、选品没方向想从需求反推、AI拓品候选验证
- 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 Bixie Amazon Unmet Demand Keyword To Product is an agent skill from xjli360/sealeap-amazon-skills. Identify keywords with rising search volume and click interest but below-benchmark conversion as unmet-demand signals, then run them through AI-assisted product-candidate generation and a market, competitive, and profitability validation gate. Rejects candidates that fail the profit or IP check before sourcing. Use for 找搜索量高转化低的词、选品没方向想从需求反推、AI拓品候选验证. Do not use to place a purchase order directly from the candidate list, or to skip the patent and compliance check.
Its SKILL.md is about 710 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 Legal & Compliance, covering Keyword research, Forms and invoices and Regulatory compliance. 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
- 找搜索量高转化低的词、选品没方向想从需求反推、AI拓品候选验证
- Place a purchase order directly from the candidate list
- Skip the patent and compliance check
Example prompts
- “/sealeap-bixie-amazon-unmet-demand-keyword-to-product”
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 Bixie Amazon Unmet Demand Keyword To Product loads about 706 tokens when it runs, and up to ~3k if it reads all its reference files. Until then it costs about 130 tokens; SKILL.md has 147 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). 147 words, ~706 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- sealeap-bixie-amazon-unmet-demand-keyword-to-product
- description
- Identify keywords with rising search volume and click interest but below-benchmark conversion as unmet-demand signals, then run them through AI-assisted product-candidate generation and a market, competitive, and profitability validation gate. Rejects candidates that fail the profit or IP check before sourcing. Use for 找搜索量高转化低的词、选品没方向想从需求反推、AI拓品候选验证. Do not use to place a purchase order directly from the candidate list, or to skip the patent and compliance check.
Amazon 未满足需求选品闭环
目标
Identify keywords with rising search volume and click interest but below-benchmark conversion as unmet-demand signals, then run them through AI-assisted product-candidate generation and a market, competitive, and profitability validation gate. Rejects candidates that fail the profit or IP check before sourcing.
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。
- 转化率低于基准里的基准本身是一个统计估算值，受价格带划分、时间窗口选择影响较大，判断前需确认基准口径与自身产品是否真正可比。
- AI 生成的产品建议是启发式候选，不能替代正式的专利检索、供应链可行性与合规审查，落地前必须补齐这些独立验证步骤。
- 搜索量上升与点击率高只反映需求信号，不代表已验证的可盈利空间，利润核算未通过前不应视为已确认机会。
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：
- 在广告后台的需求探测类功能里，筛出搜索量环比上升、点击率高于同类目均值、但转化率低于同价位基准的关键词，作为未满足需求的候选池。
- 对候选词逐个核实转化率基准的可比口径（同价格带、同产品类型），避免把跨品类或跨价位的基准直接套用。
- 用 AI 拓品工具输入候选词与相关竞品 ASIN，生成细分方向（优化现有产品解决该需求）与互补方向（围绕该需求做配套新品）两类候选。
- 对候选逐个核实市场趋势、供需比、价格带与头部竞品格局，排除趋势向下或头部垄断过强的方向。
- 结合 AI 做评论声音、关键词延展与利润核算，任何一项显示不可盈利或强负面反馈的候选直接淘汰。
- 落地前对入围候选做专利与合规初筛，存在明显风险的候选放弃或转为需要人工复核的待定项。
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：核实候选品类的市场趋势、竞品格局与评论声音作为需求验证阶段的第三方代理证据。
- 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
- 未满足需求关键词清单
- AI拓品候选分类表
- 市场验证结果表
- 利润与合规核查记录
- 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/weixin/bixie/sealeap-bixie-amazon-unmet-demand-keyword-to-product 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 Bixie Amazon Unmet Demand Keyword To Product 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 Bixie Amazon Unmet Demand Keyword To Product this skillxjli360/sealeap-amazon-skills | 251 | — | ~706 | Automated safety check: Pass | MIT | |
| Prior Art Scoutn1m21n/Infinite | 271 | — | ~1.3k | Automated safety check: Pass | Custom licence | |
| Find Law Firmjeremylongshore/tons-of-skills-marketplace | 2.8k | — | ~3.6k | Automated safety check: Notes | MIT | |
| Patsnap Ip Searchingpatsnap/mcp | 113 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Prior Art Searchillusionaireal/oh-my-patent | 104 | — | ~1.8k | Automated safety check: Pass | MIT | |
| Patsnap Triz Case Librarypatsnap/mcp | 113 | — | ~885 | Automated safety check: Pass | Apache-2.0 |
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Questions about Sealeap Bixie Amazon Unmet Demand Keyword To Product
What does Sealeap Bixie Amazon Unmet Demand Keyword To Product do?
Identify keywords with rising search volume and click interest but below-benchmark conversion as unmet-demand signals, then run them through AI-assisted product-candidate generation and a market…. Sealeap Bixie Amazon Unmet Demand Keyword To Product is an agent skill from xjli360/sealeap-amazon-skills. Identify keywords with rising search volume and click interest but below-benchmark conversion as unmet-demand signals, then run them through AI-assisted product-candidate generation and a market, competitive, and profitability validation gate.
When should I use Sealeap Bixie Amazon Unmet Demand Keyword To Product?
Sealeap Bixie Amazon Unmet Demand Keyword To Product fits situations like: 找搜索量高转化低的词、选品没方向想从需求反推、AI拓品候选验证; place a purchase order directly from the candidate list; skip the patent and compliance check.
How do I install Sealeap Bixie Amazon Unmet Demand Keyword To Product in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-bixie-amazon-unmet-demand-keyword-to-product -a claude-code`. Or copy the skill folder (amazon-skills/weixin/bixie/sealeap-bixie-amazon-unmet-demand-keyword-to-product in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Bixie Amazon Unmet Demand Keyword To Product in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-bixie-amazon-unmet-demand-keyword-to-product -a codex`. Or copy the skill folder (amazon-skills/weixin/bixie/sealeap-bixie-amazon-unmet-demand-keyword-to-product in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product in your project. Codex loads it when a task matches its description.
Can I use Sealeap Bixie Amazon Unmet Demand Keyword To Product 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-bixie-amazon-unmet-demand-keyword-to-product -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-bixie-amazon-unmet-demand-keyword-to-product, .gemini/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product, .github/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product and .opencode/skills/sealeap-bixie-amazon-unmet-demand-keyword-to-product in your project.
What does Sealeap Bixie Amazon Unmet Demand Keyword To Product need to run?
Going by SKILL.md and its folder, Sealeap Bixie Amazon Unmet Demand Keyword To Product needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Bixie Amazon Unmet Demand Keyword To Product 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 Bixie Amazon Unmet Demand Keyword To Product 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 Bixie Amazon Unmet Demand Keyword To Product use?
Sealeap Bixie Amazon Unmet Demand Keyword To Product 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 Bixie Amazon Unmet Demand Keyword To Product use?
About 706 tokens (SKILL.md is roughly 2.8k 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 2.3k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Bixie Amazon Unmet Demand Keyword To Product?
Skills that share tags, products or a category with Sealeap Bixie Amazon Unmet Demand Keyword To Product: Prior Art Scout (n1m21n/Infinite, 271 stars), Find Law Firm (jeremylongshore/tons-of-skills-marketplace, 2.8k stars), Patsnap Ip Searching (patsnap/mcp, 113 stars) and Prior Art Search (illusionaireal/oh-my-patent, 104 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sealeap Bixie Amazon Unmet Demand Keyword To Product?
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.