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eco-hotel

v3.2.0

Book flights to eco-hotel and sustainable travel destinations. Also supports: flight booking, hotel reservation, train tickets, attraction tickets, itinerary...

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Install

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Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "eco-hotel" (xiejinsong/eco-hotel) from ClawHub.
Skill page: https://clawhub.ai/xiejinsong/eco-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.

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openclaw skills install eco-hotel

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npx clawhub@latest install eco-hotel
Security Scan
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Purpose & Capability
The skill's claimed purpose (flight/hotel/train bookings for eco travel) aligns with the runtime instructions, which exclusively use a CLI named 'flyai' to perform searches and produce booking links. However the description mentions 'Fliggy (Alibaba Group)' while the instructions and CLI refer to 'flyai'/@fly-ai — a mismatch that could be a harmless copy/edit error or a sign of sloppy/opaque provenance. The skill has no homepage or source repository listed, which reduces transparency.
Instruction Scope
All runtime actions are constrained to running the flyai CLI and formatting its JSON output; the SKILL.md explicitly forbids using training data and forbids fabricating results. The instructions do not attempt to read unrelated files, env vars, or external endpoints beyond invoking the CLI. The notable behavior is the hard requirement to install and rely on an external CLI before answering, which expands the runtime surface beyond the agent itself.
!
Install Mechanism
There is no formal install spec in the skill bundle, but the SKILL.md mandates running 'npm i -g @fly-ai/flyai-cli' if the CLI is missing. Installing a global npm package from an unverified name is a moderate-to-high risk: the package is not linked to a homepage or publisher in the skill metadata, the registry owner is unknown, and global install writes binaries to the system PATH and persists. The regex scanner found nothing (no code files), so the only code pulled at runtime would be whatever the npm package provides — this is an unvetted remote code fetch.
Credentials
The skill does not request environment variables, credentials, or config paths. It does not ask for AWS/third-party tokens or secrets. From a credential perspective the requests are proportional to the stated purpose (a search/booking CLI does not inherently require extra environment secrets).
Persistence & Privilege
The skill does not set always:true and does not declare persistent privileges in metadata. However, runtime instructions instruct installing a global CLI (npm -g), which creates a persistent binary on the host. If the agent is allowed to invoke skills autonomously, it could install that CLI at first use. This combination (autonomous invocation + mandatory global install of an external package) increases the blast radius compared with a purely instruction-only skill, although it is not proof of malicious intent.
What to consider before installing
This skill is functional for its stated purpose but requires installing an unvetted global npm package (@fly-ai/flyai-cli) and lacks a homepage or source repo. Before installing or enabling: (1) verify the npm package publisher and inspect the package page and source code (or request the skill author to provide a repository/homepage); (2) prefer installing the CLI in an isolated environment (container, VM, or restricted user) rather than system-wide; (3) ask the author why the description references Fliggy/Alibaba while the CLI is 'flyai'; (4) if you cannot validate the CLI, avoid granting the agent permission to auto-install packages or run this skill autonomously. If you accept the risk, monitor the installed package and limit its network/system privileges.

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

latestvk971pbchf022k8dvsejj643zn585ed0p
57downloads
0stars
1versions
Updated 3d 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: eco-hotel

Overview

Eco Hotel Flights.

When to Activate

User query contains:

  • English: "eco hotel flight", "green travel flight", "sustainable travel", "eco resort flight", "find a hotel"
  • Chinese: "生态酒店航班", "绿色旅行机票", "环保出行", "可持续旅行", "订酒店"

Do NOT activate for: hotel → compare-hotels; nature → nature-spots

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: "eco hotel flight", "生态酒店航班"

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. Eco tip — Yunnan, Guizhou, and Sanya have certified eco-resorts
  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
"eco hotel" / "生态酒店"--sort-type 2
"green travel cheap" / "便宜绿色旅行"--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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