MCP Server Builder
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
Agent skill
Sealeap Amazon Keyword Selection And Campaign Mapping
Turn an Amazon keyword universe into a clean taxonomy and campaign map using relevance, intent, roots, negatives, and evidence from authorized reports.
MITAuto-check passed
Install Sealeap Amazon Keyword Selection And Campaign Mapping
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-keyword-selection-and-campaign-mapping -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-keyword-selection-and-campaign-mapping --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/qilin/sealeap-amazon-keyword-selection-and-campaign-mapping .claude/skills/sealeap-amazon-keyword-selection-and-campaign-mapping && 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-amazon-keyword-selection-and-campaign-mapping" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-keyword-selection-and-campaign-mapping into .claude/skills/sealeap-amazon-keyword-selection-and-campaign-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-keyword-selection-and-campaign-mapping", 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/qilin/sealeap-amazon-keyword-selection-and-campaign-mappingType 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-amazon-keyword-selection-and-campaign-mapping -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-keyword-selection-and-campaign-mapping --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/qilin/sealeap-amazon-keyword-selection-and-campaign-mapping .agents/skills/sealeap-amazon-keyword-selection-and-campaign-mapping && 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-amazon-keyword-selection-and-campaign-mapping" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-keyword-selection-and-campaign-mapping into .agents/skills/sealeap-amazon-keyword-selection-and-campaign-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-keyword-selection-and-campaign-mapping", 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-amazon-keyword-selection-and-campaign-mapping -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-keyword-selection-and-campaign-mapping --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/qilin/sealeap-amazon-keyword-selection-and-campaign-mapping .cursor/skills/sealeap-amazon-keyword-selection-and-campaign-mapping && 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-amazon-keyword-selection-and-campaign-mapping" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-keyword-selection-and-campaign-mapping into .cursor/skills/sealeap-amazon-keyword-selection-and-campaign-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-keyword-selection-and-campaign-mapping", 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/qilin/sealeap-amazon-keyword-selection-and-campaign-mapping--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-amazon-keyword-selection-and-campaign-mapping -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-amazon-keyword-selection-and-campaign-mapping --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/qilin/sealeap-amazon-keyword-selection-and-campaign-mapping .gemini/skills/sealeap-amazon-keyword-selection-and-campaign-mapping && 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-amazon-keyword-selection-and-campaign-mapping" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-keyword-selection-and-campaign-mapping into .gemini/skills/sealeap-amazon-keyword-selection-and-campaign-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-keyword-selection-and-campaign-mapping", 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-amazon-keyword-selection-and-campaign-mappingInstalls 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-amazon-keyword-selection-and-campaign-mapping -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/qilin/sealeap-amazon-keyword-selection-and-campaign-mapping .github/skills/sealeap-amazon-keyword-selection-and-campaign-mapping && 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-amazon-keyword-selection-and-campaign-mapping" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-keyword-selection-and-campaign-mapping into .github/skills/sealeap-amazon-keyword-selection-and-campaign-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-keyword-selection-and-campaign-mapping", 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-amazon-keyword-selection-and-campaign-mapping -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-amazon-keyword-selection-and-campaign-mapping --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/qilin/sealeap-amazon-keyword-selection-and-campaign-mapping .opencode/skills/sealeap-amazon-keyword-selection-and-campaign-mapping && 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-amazon-keyword-selection-and-campaign-mapping" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/douyin/qilin/sealeap-amazon-keyword-selection-and-campaign-mapping into .opencode/skills/sealeap-amazon-keyword-selection-and-campaign-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-amazon-keyword-selection-and-campaign-mapping", 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-amazon-keyword-selection-and-campaign-mapping- GitHub stars
- 251
- Token cost
- ~546 tokens
- SKILL.md length
- 84 words
- Files
- 4 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Turn an Amazon keyword universe into a clean taxonomy and campaign map using relevance, intent, roots, negatives, and evidence from authorized reports.
- Works in 6 steps: 合并与去重 → 建立词根 taxonomy → 评分排序 → …
- The user asks how to collect keywords
- 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 Amazon Keyword Selection And Campaign Mapping is an agent skill from xjli360/sealeap-amazon-skills. Turn an Amazon keyword universe into a clean taxonomy and campaign map using relevance, intent, roots, negatives, and evidence from authorized reports. Use when the user asks how to collect keywords, perform word-root analysis, choose auto versus broad versus exact targeting, or prevent broad campaigns from drifting. Produce a draft architecture and never apply ad changes without explicit approval.
Its SKILL.md is about 550 tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/mcp-data-plan.md` and `scripts/mcp_research.py`).
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
- The user asks how to collect keywords
- Perform word-root analysis
- Choose auto versus broad versus exact targeting
- Prevent broad campaigns from drifting
Example prompts
- “/sealeap-amazon-keyword-selection-and-campaign-mapping”
Requirements
- Python 3
Workflow steps
6 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 Amazon Keyword Selection And Campaign Mapping loads about 546 tokens when it runs, and up to ~2.1k if it reads all its reference files. Until then it costs about 114 tokens; SKILL.md has 84 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). 84 words, ~546 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-amazon-keyword-selection-and-campaign-mapping/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- sealeap-amazon-keyword-selection-and-campaign-mapping
- description
- Turn an Amazon keyword universe into a clean taxonomy and campaign map using relevance, intent, roots, negatives, and evidence from authorized reports. Use when the user asks how to collect keywords, perform word-root analysis, choose auto versus broad versus exact targeting, or prevent broad campaigns from drifting. Produce a draft architecture and never apply ad changes without explicit approval.
Amazon 关键词选取与广告映射
目标
把杂乱的关键词集合转成可执行的分类、否定和投放结构，使探索范围与高转化目标同时可控。
适用任务
- 竞品反查后词太多、重复多、不知道如何下手。
- 需要为新品搭建自动、广泛、词组、精准和商品投放的职责分工。
- 广泛流量跑偏，需要建立词根级前置否定。
开始前要拿到
- 产品事实表：品名、材质、功能、兼容性、尺寸、人群、场景和明确不适用项。
- 授权来源的竞品关键词、Amazon 搜索词报告、品牌分析或其他可追溯数据。
- 搜索量或代理指标、CPC、转化、订单和自然排名数据。
缺失的数据要明确列为缺口，并把结论标成事实、估算或假设；不要补造数字。
不可妥协的边界
- 竞品词不等于本品词；每个关键词必须通过产品事实和相关性复核。
- 不得购买、抓取或使用无权访问的竞品机密广告数据。
- 否定词先检查歧义和变体，避免一次词根否定误伤有效查询。
- 当前 Amazon 官方政策、帮助页、账户资格和后台实际字段优先于本 Skill 中的经验框架；规则可能变化时先核验。
- 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。
- 不输出原素材的创作者身份、账号、链接、视频编号或可反查线索；当前业务证据的官方来源、采集时间和口径仍需保留。
第三方 MCP 数据
只有在本任务确实需要外部市场、竞品、关键词或公开网页证据时，才读取 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，不照搬历史工具名。
- 凭证只从环境变量读取，不放进命令参数、URL、Skill、结果文件或 Git。
- tools/call 可能计费。调用前展示 Provider、工具名、无密钥参数、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。
- 第三方数据标为估算或代理证据，记录 Provider、工具、无密钥参数、查询时间和原始结果位置；失败一次后记录缺口，不反复消耗额度。
- 脱敏结果用 --output 写到 Skill 包之外的任务私有目录；不假设安装位置受仓库 .gitignore 保护，不把运行结果写入 Skill 包。
工作流
1. 合并与去重
统一大小写、单复数和常见拼写，保留原始来源字段，删除重复项但不丢失证据链。
2. 建立词根 taxonomy
至少区分高意图属性词根、覆盖型高频词根、通用词、品牌词、竞品词和不相关词根。
3. 评分排序
按事实相关性、购买意图、流量、竞争、预估转化和利润空间评分；缺失数据不伪造，降级为待验证。
4. 映射广告职责
自动用于受控发现，广泛或词组用于词根扩展，精准用于已验证词，商品投放用于相似详情页或类目机会。
5. 建立否定逻辑
明确哪些词做精准否定、哪些词根可做词组否定，并记录否定原因和复核人。
6. 持续迁移
按固定窗口把出单搜索词迁移、把高耗无转化词降级或否定，并同步检查广告间的重复覆盖。
判断标准
- 词库每行至少包含关键词、相关性、意图、词根、证据来源、建议投放和状态。
- 高转化只是预测时必须明确标为假设。
- 广告结构能回答每一组的探索对象、预算职责和迁移出口。
必须交付的结果
- 去重后的关键词主表。
- 词根分类、优先级和不相关词表。
- 关键词到广告类型的映射表。
- 迁移、否定和复核节奏。
结尾列出数据窗口、关键假设、证据缺口、风险和下一步；如包含待执行动作，单独放在“待批准变更”中。
© 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 3 other files (scripts, references) in amazon-skills/douyin/qilin/sealeap-amazon-keyword-selection-and-campaign-mapping of xjli360/sealeap-amazon-skills.
- SKILL.md
- agents/openai.yaml
- references/mcp-data-plan.md
- scripts/mcp_research.py
Open the folder on GitHubat commit 497d4b8
Compare with similar skills
Sealeap Amazon Keyword Selection And Campaign Mapping 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 Amazon Keyword Selection And Campaign Mapping this skillxjli360/sealeap-amazon-skills | 251 | — | ~546 | Automated safety check: Pass | MIT | |
| MCP Server Builderanthropics/skills | 180k | 63 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| MCP Server BuildershareAI-lab/learn-claude-code | 78k | 4 repos | ~1.2k | Automated safety check: Pass | MIT | |
| MCP Integration for Pluginsanthropics/claude-plugins-official | 38k | 11 repos | ~3.1k | Automated safety check: Pass | Apache-2.0 | |
| Figma use_figma Plugin API Ruleswarpdotdev/warp | 65k | 4 repos | ~4.4k | Automated safety check: Pass | AGPL-3.0 | |
| Stitch to Remotion Walkthrough Videosgoogle-labs-code/stitch-skills | 8.5k | 6 repos | ~3.2k | Automated safety check: Notes | Apache-2.0 |
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Questions about Sealeap Amazon Keyword Selection And Campaign Mapping
What does Sealeap Amazon Keyword Selection And Campaign Mapping do?
Turn an Amazon keyword universe into a clean taxonomy and campaign map using relevance, intent, roots, negatives, and evidence from authorized reports. Sealeap Amazon Keyword Selection And Campaign Mapping is an agent skill from xjli360/sealeap-amazon-skills. Turn an Amazon keyword universe into a clean taxonomy and campaign map using relevance, intent, roots, negatives, and evidence from authorized reports.
When should I use Sealeap Amazon Keyword Selection And Campaign Mapping?
Sealeap Amazon Keyword Selection And Campaign Mapping fits situations like: the user asks how to collect keywords; perform word-root analysis; choose auto versus broad versus exact targeting; prevent broad campaigns from drifting.
How do I install Sealeap Amazon Keyword Selection And Campaign Mapping in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-keyword-selection-and-campaign-mapping -a claude-code`. Or copy the skill folder (amazon-skills/douyin/qilin/sealeap-amazon-keyword-selection-and-campaign-mapping in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-amazon-keyword-selection-and-campaign-mapping in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Amazon Keyword Selection And Campaign Mapping in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-amazon-keyword-selection-and-campaign-mapping -a codex`. Or copy the skill folder (amazon-skills/douyin/qilin/sealeap-amazon-keyword-selection-and-campaign-mapping in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-amazon-keyword-selection-and-campaign-mapping in your project. Codex loads it when a task matches its description.
Can I use Sealeap Amazon Keyword Selection And Campaign Mapping 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-amazon-keyword-selection-and-campaign-mapping -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-amazon-keyword-selection-and-campaign-mapping, .gemini/skills/sealeap-amazon-keyword-selection-and-campaign-mapping, .github/skills/sealeap-amazon-keyword-selection-and-campaign-mapping and .opencode/skills/sealeap-amazon-keyword-selection-and-campaign-mapping in your project.
What does Sealeap Amazon Keyword Selection And Campaign Mapping need to run?
Going by SKILL.md and its folder, Sealeap Amazon Keyword Selection And Campaign Mapping needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Amazon Keyword Selection And Campaign Mapping 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 Amazon Keyword Selection And Campaign Mapping 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 Amazon Keyword Selection And Campaign Mapping use?
Sealeap Amazon Keyword Selection And Campaign Mapping 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 Amazon Keyword Selection And Campaign Mapping use?
About 546 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 1.5k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Amazon Keyword Selection And Campaign Mapping?
Skills that share tags, products or a category with Sealeap Amazon Keyword Selection And Campaign Mapping: MCP Server Builder (anthropics/skills, 180k stars), MCP Server Builder (shareAI-lab/learn-claude-code, 78k stars), MCP Integration for Plugins (anthropics/claude-plugins-official, 38k stars) and Figma use_figma Plugin API Rules (warpdotdev/warp, 65k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sealeap Amazon Keyword Selection And Campaign Mapping?
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.