Remnic Search
joshuaswarren/remnic
Run a deep full-text search across every Remnic memory. An agent skill from joshuaswarren/remnic.
Agent skill
Sealeap Tianlu Amazon AI Readable Title Structure
Restructure product titles from keyword-stuffed strings into a semantically ordered two-part layout (brand plus core category and attributes first, then differentiating function and use-case terms)…
Install Sealeap Tianlu Amazon AI Readable Title Structure
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-tianlu-amazon-ai-readable-title-structure -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-tianlu-amazon-ai-readable-title-structure --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/tianlu/sealeap-tianlu-amazon-ai-readable-title-structure .claude/skills/sealeap-tianlu-amazon-ai-readable-title-structure && 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-tianlu-amazon-ai-readable-title-structure" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/weixin/tianlu/sealeap-tianlu-amazon-ai-readable-title-structure into .claude/skills/sealeap-tianlu-amazon-ai-readable-title-structure/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-tianlu-amazon-ai-readable-title-structure", 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/tianlu/sealeap-tianlu-amazon-ai-readable-title-structureType 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-tianlu-amazon-ai-readable-title-structure -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-tianlu-amazon-ai-readable-title-structure --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/tianlu/sealeap-tianlu-amazon-ai-readable-title-structure .agents/skills/sealeap-tianlu-amazon-ai-readable-title-structure && 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-tianlu-amazon-ai-readable-title-structure" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/weixin/tianlu/sealeap-tianlu-amazon-ai-readable-title-structure into .agents/skills/sealeap-tianlu-amazon-ai-readable-title-structure/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-tianlu-amazon-ai-readable-title-structure", 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-tianlu-amazon-ai-readable-title-structure -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-tianlu-amazon-ai-readable-title-structure --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/tianlu/sealeap-tianlu-amazon-ai-readable-title-structure .cursor/skills/sealeap-tianlu-amazon-ai-readable-title-structure && 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-tianlu-amazon-ai-readable-title-structure" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/weixin/tianlu/sealeap-tianlu-amazon-ai-readable-title-structure into .cursor/skills/sealeap-tianlu-amazon-ai-readable-title-structure/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-tianlu-amazon-ai-readable-title-structure", 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/tianlu/sealeap-tianlu-amazon-ai-readable-title-structure--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-tianlu-amazon-ai-readable-title-structure -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xjli360/sealeap-amazon-skills sealeap-tianlu-amazon-ai-readable-title-structure --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/tianlu/sealeap-tianlu-amazon-ai-readable-title-structure .gemini/skills/sealeap-tianlu-amazon-ai-readable-title-structure && 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-tianlu-amazon-ai-readable-title-structure" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/weixin/tianlu/sealeap-tianlu-amazon-ai-readable-title-structure into .gemini/skills/sealeap-tianlu-amazon-ai-readable-title-structure/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-tianlu-amazon-ai-readable-title-structure", 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-tianlu-amazon-ai-readable-title-structureInstalls 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-tianlu-amazon-ai-readable-title-structure -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/tianlu/sealeap-tianlu-amazon-ai-readable-title-structure .github/skills/sealeap-tianlu-amazon-ai-readable-title-structure && 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-tianlu-amazon-ai-readable-title-structure" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/weixin/tianlu/sealeap-tianlu-amazon-ai-readable-title-structure into .github/skills/sealeap-tianlu-amazon-ai-readable-title-structure/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-tianlu-amazon-ai-readable-title-structure", 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-tianlu-amazon-ai-readable-title-structure -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-tianlu-amazon-ai-readable-title-structure --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/tianlu/sealeap-tianlu-amazon-ai-readable-title-structure .opencode/skills/sealeap-tianlu-amazon-ai-readable-title-structure && 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-tianlu-amazon-ai-readable-title-structure" agent skill from https://github.com/xjli360/sealeap-amazon-skills/tree/main/amazon-skills/weixin/tianlu/sealeap-tianlu-amazon-ai-readable-title-structure into .opencode/skills/sealeap-tianlu-amazon-ai-readable-title-structure/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sealeap-tianlu-amazon-ai-readable-title-structure", 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-tianlu-amazon-ai-readable-title-structure- GitHub stars
- 251
- Token cost
- ~841 tokens
- SKILL.md length
- 172 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 179
- Repo updated
- First seen
- Licence
- MIT
At a glance
Restructure product titles from keyword-stuffed strings into a semantically ordered two-part layout (brand plus core category and attributes first, then differentiating function and use-case terms)…
- 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。 → …
- 标题关键词堆砌整改、语义化标题结构改写、新品上架标题起草
- 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 Tianlu Amazon AI Readable Title Structure is an agent skill from xjli360/sealeap-amazon-skills. Restructure product titles from keyword-stuffed strings into a semantically ordered two-part layout (brand plus core category and attributes first, then differentiating function and use-case terms), then validate each candidate term's real search relevance through storefront search evidence and keyword-volume data before committing. Treats the premise that stuffed titles now carry an algorithmic penalty as an unverified hypothesis to test with the account's own indexing and conversion data, not an established…
Its SKILL.md is about 840 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 Backend & APIs, covering Search implementation. 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
- 标题关键词堆砌整改、语义化标题结构改写、新品上架标题起草
- Assume any claimed algorithm change is official Amazon policy without independent evidence from the accounts own search and conversion data
Example prompts
- “/sealeap-tianlu-amazon-ai-readable-title-structure”
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 Tianlu Amazon AI Readable Title Structure loads about 841 tokens when it runs, and up to ~3.2k if it reads all its reference files. Until then it costs about 191 tokens; SKILL.md has 172 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). 172 words, ~841 tokens.
Download SKILL.mdSave it as
.claude/skills/sealeap-tianlu-amazon-ai-readable-title-structure/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- sealeap-tianlu-amazon-ai-readable-title-structure
- description
- Restructure product titles from keyword-stuffed strings into a semantically ordered two-part layout (brand plus core category and attributes first, then differentiating function and use-case terms), then validate each candidate term's real search relevance through storefront search evidence and keyword-volume data before committing. Treats the premise that stuffed titles now carry an algorithmic penalty as an unverified hypothesis to test with the account's own indexing and conversion data, not an established rule. Use for 标题关键词堆砌整改、语义化标题结构改写、新品上架标题起草. Do not use to assume any claimed algorithm change is official Amazon policy without independent evidence from the account's own search and conversion data.
Amazon 标题语义结构化改写
目标
Restructure product titles from keyword-stuffed strings into a semantically ordered two-part layout (brand plus core category and attributes first, then differentiating function and use-case terms), then validate each candidate term's real search relevance through storefront search evidence and keyword-volume data before committing. Treats the premise that stuffed titles now carry an algorithmic penalty as an unverified hypothesis to test with the account's own indexing and conversion data, not an established rule.
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。
- 算法转向语义可读是来源自身的市场解读，未见官方公告或政策文本支持，需当作待验证假设，不作为标题必须改写的依据。
- 关键词研究与搜索热度核对建议使用当前可用的关键词工具或后台数据，具体使用哪款工具由账户自身情况决定，不代表对某一特定第三方产品的依赖。
- 标题结构调整对排名与转化的影响需要以自身账户的实际数据验证，来源给出的示例转换不能保证在其他类目或账户上同样有效。
先判断任务模式
- 诊断：读取现状、证据和缺口，不生成线上写入动作。
- 方案草案：输出可审核的结构、参数范围、实验和回退值。
- 执行准备：只生成待批准变更表或 API/控制台操作草案。
- 已批准执行：仅对用户在当前会话明确批准的对象和字段执行，并立即回读核验。
用户未指定时采用“诊断”。
开始前要拿到
- marketplace、产品事实、ASIN/SKU 与目标购买意图
- 本品和可比竞品的关键词、自然位置、广告可见度与采样时间
- 搜索词报告、转化、CPC、订单、利润和 Listing 当前覆盖
- 站点语言、变体、价格、库存与同期促销记录
缺失项必须标为 NEEDS_EVIDENCE；不得猜数字、补属性或把不同站点、ASIN、变体、币种和时间窗混在一起。
工作流
先读取 references/playbook.md，确认该方法适用于当前对象。按以下顺序执行：
- 核对当前标题是否存在词汇冗余堆砌、场景词混杂、修饰逻辑断裂等问题，逐条标出待精简或待重排的部分，而不是整体推翻重写。
- 按品牌加核心品类词加关键属性在前、功能卖点加差异化描述加场景词在后的两段式结构重新组织候选标题，确保信息层级从主到次清晰排列。
- 用后台搜索词建议、店铺内搜索框自动补全等一方或代理证据核对候选词是否为真实被检索的高频词，剔除凭感觉堆砌但无实际搜索量支撑的修饰词。
- 核对新标题是否仍完整覆盖原有的核心属性与合规必填信息（型号、数量、安全相关信息等），避免为追求简洁而漏掉必要属性。
- 小范围替换标题后观察自然排名与点击转化的变化，作为验证结构化标题是否优于堆砌式标题这一假设的实际证据，而不是直接全量替换。
- 若指标未见改善或出现下滑，评估是否回退旧标题或调整两段式结构的具体权重分配，把本次调整当作可回退的单变量实验对待。
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：补充候选标题词的搜索热度与相关词代理数据，用于核实结构化后的候选词是否为真实被检索的高频词，而非仅凭主观判断保留。
- 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
- 现有标题问题诊断清单
- 两段式候选标题草案
- 候选词搜索相关性核对记录
- 标题替换前后指标对比与回退判断
- 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/tianlu/sealeap-tianlu-amazon-ai-readable-title-structure 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 Tianlu Amazon AI Readable Title Structure 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 Tianlu Amazon AI Readable Title Structure this skillxjli360/sealeap-amazon-skills | 251 | — | ~841 | Automated safety check: Pass | MIT | |
| Remnic Searchjoshuaswarren/remnic | 218 | — | ~562 | Automated safety check: Pass | MIT | |
| Pp Benzingamvanhorn/printing-press-library | 2.1k | — | ~6k | Automated safety check: Notes | Apache-2.0 | |
| Engraphdevwhodevs/engraph | 171 | — | ~792 | Automated safety check: Pass | MIT | |
| Neon Postgresusenotra/notra | 260 | — | ~4.1k | Automated safety check: Notes | AGPL-3.0 | |
| Neon Postgresneondatabase/agent-skills | 100 | — | ~4.1k | Automated safety check: Notes | Apache-2.0 |
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Questions about Sealeap Tianlu Amazon AI Readable Title Structure
What does Sealeap Tianlu Amazon AI Readable Title Structure do?
Restructure product titles from keyword-stuffed strings into a semantically ordered two-part layout (brand plus core category and attributes first, then differentiating function and use-case terms)…. Sealeap Tianlu Amazon AI Readable Title Structure is an agent skill from xjli360/sealeap-amazon-skills. Restructure product titles from keyword-stuffed strings into a semantically ordered two-part layout (brand plus core category and attributes first, then differentiating function and use-case terms), then validate each candidate term's real search relevance through storefront search evidence and keyword-volume data before committing.
When should I use Sealeap Tianlu Amazon AI Readable Title Structure?
Sealeap Tianlu Amazon AI Readable Title Structure fits situations like: 标题关键词堆砌整改、语义化标题结构改写、新品上架标题起草; assume any claimed algorithm change is official Amazon policy without independent evidence from the accounts own search and conversion data.
How do I install Sealeap Tianlu Amazon AI Readable Title Structure in Claude Code?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-tianlu-amazon-ai-readable-title-structure -a claude-code`. Or copy the skill folder (amazon-skills/weixin/tianlu/sealeap-tianlu-amazon-ai-readable-title-structure in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-tianlu-amazon-ai-readable-title-structure in your project. Claude Code loads it when a task matches its description.
How do I install Sealeap Tianlu Amazon AI Readable Title Structure in Codex?
Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-tianlu-amazon-ai-readable-title-structure -a codex`. Or copy the skill folder (amazon-skills/weixin/tianlu/sealeap-tianlu-amazon-ai-readable-title-structure in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-tianlu-amazon-ai-readable-title-structure in your project. Codex loads it when a task matches its description.
Can I use Sealeap Tianlu Amazon AI Readable Title Structure 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-tianlu-amazon-ai-readable-title-structure -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-tianlu-amazon-ai-readable-title-structure, .gemini/skills/sealeap-tianlu-amazon-ai-readable-title-structure, .github/skills/sealeap-tianlu-amazon-ai-readable-title-structure and .opencode/skills/sealeap-tianlu-amazon-ai-readable-title-structure in your project.
What does Sealeap Tianlu Amazon AI Readable Title Structure need to run?
Going by SKILL.md and its folder, Sealeap Tianlu Amazon AI Readable Title Structure needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Sealeap Tianlu Amazon AI Readable Title Structure 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 Tianlu Amazon AI Readable Title Structure 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 Tianlu Amazon AI Readable Title Structure use?
Sealeap Tianlu Amazon AI Readable Title Structure 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 Tianlu Amazon AI Readable Title Structure use?
About 841 tokens (SKILL.md is roughly 3.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.4k tokens, read only when the agent opens those files.
What are the alternatives to Sealeap Tianlu Amazon AI Readable Title Structure?
Skills that share tags, products or a category with Sealeap Tianlu Amazon AI Readable Title Structure: Remnic Search (joshuaswarren/remnic, 218 stars), Pp Benzinga (mvanhorn/printing-press-library, 2.1k stars), Engraph (devwhodevs/engraph, 171 stars) and Neon Postgres (usenotra/notra, 260 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sealeap Tianlu Amazon AI Readable Title Structure?
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.