Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add malue-ai/dazee-small --skill travel-plannergit clone --depth 1 https://github.com/malue-ai/dazee-smallWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/malue-ai/dazee-small/travel-planner)<a href="https://agentmods.dev/skills/malue-ai/dazee-small/travel-planner"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/travel-planner/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/malue-ai/dazee-small/travel-planner"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/travel-planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00029 | $0.00762 |
| Opus 5 | $0.00015 | $0.00381 |
| Sonnet 5 | $0.00006 | $0.00152 |
| Haiku 4.5 | $0.00003 | $0.00076 |
Grade A, and why
travel-planner scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
旅行规划
帮助用户规划旅行：行程安排、打包清单、预算估算、当地攻略。
使用场景
- 用户说「帮我规划一个东京 5 天的行程」「周末去哪里玩」
- 用户说「帮我做个打包清单」「带什么衣服」
- 用户说「估算一下这趟旅行大概花多少钱」
执行方式
直接使用 LLM 能力规划行程，可配合 搜索类 Skill（如 jina-reader 或 web_search 工具）获取最新信息。
行程规划模板
# [目的地] [天数] 日行程
**旅行日期**: YYYY-MM-DD ~ YYYY-MM-DD
**预计预算**: $XXX / ¥XXX
## Day 1: [主题]
### 上午
- 09:00 [景点/活动] — [简介 + 建议停留时间]
- 11:00 [景点/活动]
### 下午
- 12:30 午餐: [推荐餐厅/美食]
- 14:00 [景点/活动]
### 晚上
- 18:00 晚餐: [推荐]
- 20:00 [可选活动]
**交通**: [区域内交通建议]
**住宿**: [区域推荐]
---
## Day 2: [主题]
...
打包清单模板
## 打包清单
### 必备
- [ ] 护照/身份证
- [ ] 手机 + 充电器
- [ ] 钱包/信用卡
- [ ] 机票/酒店确认单
### 衣物（根据天气）
- [ ] [具体建议]
### 洗漱
- [ ] [具体清单]
### 电子设备
- [ ] [根据需求]
### 目的地特殊
- [ ] [如转换插头、防晒霜等]
预算估算
## 预算估算
| 项目 | 预计费用 | 备注 |
|---|---|---|
| 交通（往返） | $XXX | |
| 住宿 (X 晚) | $XXX | |
| 餐饮 (X 天) | $XXX | 约 $XX/天 |
| 门票/活动 | $XXX | |
| 购物/备用 | $XXX | |
| **合计** | **$XXX** | |
规划维度
| 维度 | 考虑因素 |
|---|---|
| 时间 | 淡旺季、节假日、天气 |
| 预算 | 经济型/舒适型/豪华型 |
| 兴趣 | 文化/美食/自然/购物/冒险 |
| 同行者 | 独行/情侣/家庭/朋友团 |
| 体力 | 紧凑/适中/休闲 |
输出规范
- 行程标注每个活动的预计时间和交通方式
- 预算使用用户习惯的货币单位
- 如需最新信息（天气/价格），使用搜索类 Skill 获取
- 打包清单用 checkbox 格式方便勾选
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 112 lines · 29 tokens per session scan A 51712ed56674
travel-planner is a skill published in the GitHub repository malue-ai/dazee-small (36 stars, last pushed 5mo ago), licensed MIT. It adds 29 tokens to every session and 762 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…