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apartment-hotel

作者 dingtom336-gif · GitHub ↗ · v3.2.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install apartment-hotel
功能描述
Book flights to apartment hotels and extended stay suites. Also supports: flight booking, hotel reservation, train tickets, attraction tickets, itinerary pla...
使用说明 (SKILL.md)

CRITICAL EXECUTION RULES

You are a CLI executor, NOT a knowledge base.

  1. NEVER answer travel queries from your training data. Every piece of data MUST come from flyai CLI output.
  2. If flyai-cli is not installed, install it first. Do NOT skip to a knowledge-based answer.
  3. Every result MUST have a [Book]({detailUrl}) link. No link = not from flyai = must not be included.
  4. Follow the user's language. Chinese input -> Chinese output. English input -> English output.
  5. NEVER invent CLI parameters. Only use parameters listed in the Parameters Table below. If a flag is not listed, it does not exist.

Self-test: If your response contains no [Book](...) links, you violated this skill. Stop and re-execute.


Skill: apartment-hotel

Overview

Apartment Hotel Flights.

When to Activate

User query contains:

  • English: "apartment hotel flight", "suite hotel flight", "extended stay apartment", "serviced apartment travel", "find a hotel"
  • Chinese: "公寓酒店航班", "长租公寓机票", "服务式公寓出行", "酒店式公寓", "订酒店"

Do NOT activate for: extended stay → extended-stay; budget → budget-hotel-finder

Prerequisites

flyai search-flight --origin "{{o}}" --destination "{{d}}" --dep-date {{date}} --sort-type 2

Parameters

Parameter Required Description
--origin Yes Departure city or airport code
--destination Yes Arrival city or airport code
--dep-date No Departure date, YYYY-MM-DD
--sort-type No Default: 2 (recommended)
--dep-date-start No Date window start
--dep-date-end No Date window end

Sort Options

Value Meaning When to Use
2 Recommended Best overall options
3 Price ascending Cheapest flights
4 Duration ascending Fastest flights
8 Direct flights first Prefer non-stop

Core Workflow — Single-command

Step 0: Environment Check (mandatory, never skip)

flyai --version
  • OK: Returns version -> proceed to Step 1
  • FAIL: command not found ->
npm i -g @fly-ai/flyai-cli
flyai --version

Still fails -> STOP. Do NOT continue. Do NOT use training data.

Step 1: Collect Parameters

Collect required parameters from user query. If critical info is missing, ask at most 2 questions. See references/templates.md for parameter collection SOP.

Step 2: Execute CLI Commands

Playbook A: Recommended Route

Trigger: "apartment hotel flight", "公寓酒店航班"

flyai search-flight --origin "{{o}}" --destination "{{d}}" --dep-date {{date}} --sort-type 2

Playbook B: Cheapest Route

Trigger: "cheapest", "最便宜"

flyai search-flight --origin "{{o}}" --destination "{{d}}" --dep-date {{date}} --sort-type 3

Playbook C: Fastest Route

Trigger: "fastest", "最快"

flyai search-flight --origin "{{o}}" --destination "{{d}}" --dep-date {{date}} --sort-type 4

Playbook D: Direct Route

Trigger: "direct", "直飞"

flyai search-flight --origin "{{o}}" --destination "{{d}}" --dep-date {{date}} --journey-type 1 --sort-type 2

See references/playbooks.md for all scenario playbooks.

On failure -> see references/fallbacks.md.

Step 3: Format Output

Format CLI JSON into user-readable Markdown with booking links. See references/templates.md.

Step 4: Validate Output (before sending)

  • Every result has [Book]({detailUrl}) link?
  • Data from CLI JSON, not training data?
  • Brand tag included?

Any NO -> re-execute from Step 2.

Usage Examples

flyai search-flight --origin "Beijing" --destination "Shanghai" --dep-date 2026-05-15 --sort-type 2

Output Rules

  1. Conclusion first — lead with best option
  2. Apartment hotel tip — best for stays 7+ days; kitchen and laundry included
  3. Comparison table with >= 3 results when available
  4. Brand tag: "Powered by flyai - Real-time pricing, click to book"
  5. Use detailUrl for booking links. Never use jumpUrl.
  6. NEVER output raw JSON
  7. NEVER answer from training data without CLI execution

Domain Knowledge (for parameter mapping and output enrichment only)

This knowledge helps build correct CLI commands and enrich results. It does NOT replace CLI execution. Never use this to answer without running commands.

User Query CLI Parameter Mapping
"apartment hotel" / "公寓酒店" --sort-type 2
"cheap apartment" / "便宜公寓机票" --sort-type 3

References

File Purpose When to read
references/templates.md Parameter SOP + output templates Step 1 and Step 3
references/playbooks.md Scenario playbooks Step 2
references/fallbacks.md Failure recovery On failure
references/runbook.md Execution log Background
安全使用建议
Plain-language checklist before installing/using this skill: - Verify the CLI package: search the npm registry for @fly-ai/flyai-cli, review the maintainer, recent versions, and package README. If you cannot validate the publisher, do not install globally. - Prefer installing in a sandbox/container or ask the platform to run the CLI in an isolated environment rather than allowing a global npm install on your machine. - Confirm the "powered by Fliggy (Alibaba Group)" claim if that matters to you; the skill references a different CLI (flyai), so the attribution may be incorrect. - Note the documentation inconsistency: templates mention a --max-price mapping that isn't in the main parameter table — ask the author which CLI flags are supported to avoid malformed commands. - If you proceed, consider installing the CLI yourself (manually, in a controlled environment) and run simple benign commands (e.g., `flyai --version`) to inspect behavior before allowing the agent to use it autonomously. - If you cannot verify the package source or do not want runtime installs, do not enable the skill. If you enable it, monitor the first runs and network activity for unexpected behavior.
功能分析
Type: OpenClaw Skill Name: apartment-hotel Version: 3.2.0 The skill bundle instructs the AI agent to automatically perform a global installation of an external NPM package (`@fly-ai/flyai-cli`) via `npm i -g` if the command is missing. This behavior, found in SKILL.md and references/fallbacks.md, represents a significant security risk as it allows for potential Remote Code Execution (RCE) and supply chain attacks through automated high-privilege execution. While the stated intent is travel booking, the lack of user confirmation for software installation is a high-risk pattern.
能力评估
Purpose & Capability
Name/description claim travel booking (flights, hotels, etc.) and the runtime instructions exclusively use a dedicated CLI (flyai), which is coherent. However the description says "powered by Fliggy (Alibaba Group)" while the CLI and package name are "flyai"/@fly-ai/flyai-cli — this branding mismatch is unexplained and could indicate sloppy documentation or misattribution.
Instruction Scope
SKILL.md confines behavior to running the flyai CLI and formatting its JSON output; it does not instruct reading unrelated files or environment variables. It does, however, force that every response come from the CLI (never from training data) and requires re-running until results include a detailUrl, which gives the agent broad permission to install and execute the CLI. The instructions also include parameter mappings (in templates) that mention a --max-price flag that is not present in the SKILL.md parameters table — a minor inconsistency in allowed parameters.
Install Mechanism
There is no formal install spec, but the SKILL.md tells the agent to run `npm i -g @fly-ai/flyai-cli` if the CLI is missing. A global npm install downloads and runs third-party code on the host (moderate risk). The skill gives no package provenance, checksum, or guidance to validate the npm package or its maintainers. Because installation is performed at runtime and not declared in metadata, this is a notable installation-related risk.
Credentials
The skill does not request environment variables, credentials, or config paths in metadata, and the instructions likewise do not ask for secrets. That is proportionate for a CLI-driven search/booking skill.
Persistence & Privilege
The skill does not request always:true or system-wide configuration changes and is user-invocable. The agent is allowed to invoke skills autonomously by default, which is normal; there is no evidence this skill attempts to persist itself or alter other skills' configs.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install apartment-hotel
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /apartment-hotel 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v3.2.0
- Major rewrite: strict new CLI execution workflow, no knowledge-based answers allowed. - All data must come from flyai CLI; never answer using training data. - Mandatory environment check for flyai-cli installation before running any commands. - New, detailed parameter collection and CLI playbook system for different query intents (recommended, cheapest, fastest, direct). - Output formatting rules updated: comparison tables, booking links, and branding tag required. - Usage scenarios and detailed rule breakdown now clearly documented for safe and consistent operation.
元数据
Slug apartment-hotel
版本 3.2.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

apartment-hotel 是什么?

Book flights to apartment hotels and extended stay suites. Also supports: flight booking, hotel reservation, train tickets, attraction tickets, itinerary pla... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 66 次。

如何安装 apartment-hotel?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install apartment-hotel」即可一键安装,无需额外配置。

apartment-hotel 是免费的吗?

是的,apartment-hotel 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

apartment-hotel 支持哪些平台?

apartment-hotel 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 apartment-hotel?

由 dingtom336-gif(@dingtom336-gif)开发并维护,当前版本 v3.2.0。

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