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hostel-finder

v3.2.0

Book flights to destinations with backpacker hostels and budget accommodations. Also supports: flight booking, hotel reservation, train tickets, attraction t...

0· 63·0 current·0 all-time

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/hostel-finder.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "hostel-finder" (dingtom336-gif/hostel-finder) from ClawHub.
Skill page: https://clawhub.ai/dingtom336-gif/hostel-finder
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

Bare skill slug

openclaw skills install hostel-finder

ClawHub CLI

Package manager switcher

npx clawhub@latest install hostel-finder
Security Scan
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Suspicious
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OpenClawOpenClaw
Suspicious
medium confidence
Purpose & Capability
The skill claims to provide flight/hostel booking and its instructions consistently require a dedicated 'flyai' CLI to perform searches — this is coherent. However, the registry metadata has no source/homepage and the CLI package (@fly-ai/flyai-cli) is unverified in the package text, so provenance is unclear.
!
Instruction Scope
Instructions mandate always sourcing results from the flyai CLI (never use training data), require installing the CLI if missing, and force a self-test that re-executes if a booking link is not present. That strict re-execution requirement could cause repeated command/install attempts or loops if the CLI returns no results. The instructions do not request unrelated files or credentials, which is good.
!
Install Mechanism
Although the skill is instruction-only, it tells the agent to run 'npm i -g @fly-ai/flyai-cli' at runtime. Installing a global npm package is a moderate risk (network download and code execution). No homepage, repo link, or checksum is provided to validate the package or publisher, increasing risk.
Credentials
The skill requests no environment variables, credentials, or config paths beyond installing a CLI. It does not ask for unrelated secrets. Note: global npm install may require elevated privileges on some systems — the skill does not describe safe alternatives (e.g., local install or sandbox).
Persistence & Privilege
The skill does not request always:true, does not modify other skills' configs, and has no install-time spec writing to system paths in the manifest. The only persistence risk is the runtime npm install the instructions request.
What to consider before installing
This skill is internally coherent for a CLI-based flight/hostel search, but it requires installing an unverified global npm package at runtime and enforces re-running until a booking link appears. Before installing or allowing the agent to run npm install: 1) Ask the skill author for the flyai CLI's official homepage/repository and publisher info and verify the @fly-ai/flyai-cli package on the npm registry (check publisher, weekly downloads, and source repository). 2) Prefer installing the CLI in an isolated environment (container, VM, or sandbox) or request a local/non-global install command instead of a -g global install. 3) Be cautious about letting the agent auto-run installs — consider disabling autonomous invocation until provenance is verified. 4) Understand the self-test/re-execution rule could cause repeated installs or loops if the CLI returns no booking links; ask the author to remove or soften that behavior. If you cannot verify the CLI package and publisher, do not install or run this skill on a production or privileged machine.

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

latestvk97fgm0vzde11fhyhjf3mhp7mh85etkg
63downloads
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: hostel-finder

Overview

Hostel Flights.

When to Activate

User query contains:

  • English: "hostel flight", "backpacker hostel flight", "budget accommodation travel", "youth hostel trip", "hostel travel"
  • Chinese: "青旅航班", "青年旅舍机票", "背包客住宿出行", "经济住宿旅行", "出行预订"

Do NOT activate for: budget → budget-hotel-finder; budget trip → budget-backpacker

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: 3 (recommended)
--max-priceNoPrice ceiling in CNY

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: "hostel flight", "青旅航班"

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

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 3

Output Rules

  1. Conclusion first — lead with best option
  2. Hostel tip — Chengdu, Chongqing, and Kunming have top-rated hostels
  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
"hostel trip" / "青旅出行"--sort-type 3 --max-price 800
"cheap hostel flight" / "便宜青旅机票"--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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