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boutique-hotel

v3.2.0

Book flights to boutique hotels and designer stay destinations. Also supports: flight booking, hotel reservation, train tickets, attraction tickets, itinerar...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for dingtom336-gif/boutique-hotel.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "boutique-hotel" (dingtom336-gif/boutique-hotel) from ClawHub.
Skill page: https://clawhub.ai/dingtom336-gif/boutique-hotel
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

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openclaw skills install boutique-hotel

ClawHub CLI

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npx clawhub@latest install boutique-hotel
Security Scan
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Purpose & Capability
Name/description claim flight & hotel booking; runtime instructions consistently require a flight-search CLI (flyai) and use commands like flyai search-flight to satisfy that purpose. The skill does not request unrelated environment variables or config paths. Minor note: description mentions 'powered by Fliggy (Alibaba Group)' while the CLI package referenced is '@fly-ai/flyai-cli' (no explicit linkage to Fliggy), which could be just a branding mismatch but is worth verifying.
!
Instruction Scope
SKILL.md tightly restricts answers to results produced by the flyai CLI and mandates installing and using that CLI; it forbids using training data or invented CLI parameters. However, there are inconsistencies across files: references/playbooks.md calls flyai keyword-search (a command not listed in the main Parameters table) and references/templates.md maps flags like --max-price and --seat-class-name that are not present in the primary Parameters table. The skill also enforces a 'self-test' that forces re-execution if a [Book](...) link is missing, which could cause repeated CLI runs. These inconsistencies expand the agent's discretion and could lead to unexpected command usage or repeated installs/executions.
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Install Mechanism
The skill has no formal install spec, but the runtime instructions explicitly tell the agent to run `npm i -g @fly-ai/flyai-cli` if flyai is not found. That means at runtime the agent may perform a global npm install from an unreviewed package name. Installing arbitrary third‑party npm packages globally is higher risk (writes to disk, creates executables, runs remote code). The SKILL.md provides no additional provenance, checksum, or official release URL for the CLI package to validate its trustworthiness.
Credentials
The skill requests no environment variables, secrets, or config paths. There is no apparent need for cloud credentials or unrelated tokens to perform the described CLI-based flight searches, so the lack of credential requests is proportionate.
Persistence & Privilege
always:false and the skill is user-invocable (normal). However, the instructions ask the agent to perform a global npm install if the CLI is missing — that is a persistent system change outside the skill's own files (creating a global CLI binary). While not an explicit permissions escalation within skill metadata, it does persist code on the host and therefore increases the blast radius if the installed package were malicious or updated. Also the skill allows autonomous invocation by default (disable-model-invocation: false), which combined with runtime installs is worth noting.
What to consider before installing
Before installing or letting the agent run this skill, consider the following: 1) The skill requires installing an npm package at runtime (npm i -g @fly-ai/flyai-cli). Verify the package on the npm registry (author, weekly downloads, repository URL, published files, and any README/source) and review its source code before allowing a global install. 2) Because the SKILL.md instructs the agent to install and execute a CLI, prefer to perform the install manually in a controlled environment (sandbox, VM, container) and inspect the binary/package behavior. 3) Note small inconsistencies in the skill (undocumented commands like flyai keyword-search and template flags such as --max-price) — ask the skill author for authoritative CLI docs or a signed release link. 4) If you cannot validate the CLI's provenance, do not grant the agent permission to execute installs or run the CLI; instead ask for an API-based integration or a vendor-backed plugin with verified distribution. 5) This skill does not request credentials, which lowers risk, but global installs and forced CLI execution can still modify your system — proceed only after manual verification or within a sandbox.

Like a lobster shell, security has layers — review code before you run it.

latestvk976vkvtht41yfsnfhfg53zp1d85eprx
59downloads
0stars
1versions
Updated 4d ago
v3.2.0
MIT-0

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: boutique-hotel

Overview

Boutique Hotel Flights.

When to Activate

User query contains:

  • English: "boutique hotel flight", "designer hotel flight", "lifestyle hotel travel", "artisan hotel trip", "find a hotel"
  • Chinese: "精品酒店航班", "设计师酒店机票", "民宿出行", "特色酒店", "订酒店"

Do NOT activate for: design hotel → design-hotel; luxury → luxury-hotel

Prerequisites

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

Parameters

ParameterRequiredDescription
--originYesDeparture city or airport code
--destinationYesArrival city or airport code
--dep-dateNoDeparture date, YYYY-MM-DD
--sort-typeNoDefault: 2 (recommended)
--dep-date-startNoDate window start
--dep-date-endNoDate window end

Sort Options

ValueMeaningWhen to Use
2RecommendedBest overall options
3Price ascendingCheapest flights
4Duration ascendingFastest flights
8Direct flights firstPrefer 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: "boutique hotel flight", "精品酒店航班"

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. Boutique tip — Suzhou, Hangzhou, and Chengdu have top boutique hotels
  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 QueryCLI Parameter Mapping
"boutique hotel" / "精品酒店"--sort-type 2
"cheap boutique" / "便宜精品酒店"--sort-type 3

References

FilePurposeWhen to read
references/templates.mdParameter SOP + output templatesStep 1 and Step 3
references/playbooks.mdScenario playbooksStep 2
references/fallbacks.mdFailure recoveryOn failure
references/runbook.mdExecution logBackground

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