family-hotel

Find hotels perfect for families — multi-bed rooms, kid-friendly amenities, nearby playgrounds, and family-oriented services. Also supports: flight booking,...

Security Scan

The skill is internally consistent: it wraps a third‑party CLI (flyai-cli) to return real‑time hotel results and does not request unrelated credentials, but it relies on installing an external npm CLI and writes/retains execution logs which you should review before using.

Purpose & Capability

Name/description match the instructions: SKILL.md only instructs running flyai CLI commands (search-hotel, keyword-search, etc.) and formatting the output. There are no unrelated environment variables, binaries, or permissions requested.

Instruction Scope

Runtime instructions require always sourcing results from flyai CLI output (never training data) and enforce specific formatting and link use. The runbook instructs logging request_id, user_query and CLI calls and suggests persisting logs to .flyai-execution-log.json if filesystem writes are available — this will store user queries and metadata locally and could contain sensitive info.

Install Mechanism

No install spec in the skill bundle, but the skill mandatorily directs installing @fly-ai/flyai-cli via 'npm i -g'. Installing a global npm package runs code from the package registry; verify the package source/trustworthiness before allowing automated installation or perform the install manually in a controlled environment.

Credentials

The skill itself declares no environment variables or credentials (proportionate). However, the flyai CLI that the skill depends on may require its own credentials or configuration not declared here, and runtime logs include raw user_query values. Expect that sensitive travel data (names, dates, destinations) may be written to logs.

Persistence & Privilege

always:false and no cross-skill config changes (good). The runbook's suggested log persistence (appending to .flyai-execution-log.json) gives the skill the ability to write persistent files in the agent working directory; this is reasonable for audit but is persistent storage of user inputs and should be considered when using the skill in sensitive contexts.

Assessment

This skill is a wrapper for the flyai CLI and is coherent with its description, but before installing or running it: 1) Verify the authenticity of the @fly-ai/flyai-cli npm package (check the package repo, publisher, and recent activity) — installing global npm packages executes code on your system. 2) Prefer installing the CLI manually in a sandbox or VM rather than allowing an agent to run 'npm i -g' automatically. 3) Be aware the skill's runbook suggests writing execution logs (including your raw queries) to .flyai-execution-log.json in the working directory — if you handle sensitive personal data, avoid running this in environments where those files could be exposed. 4) The skill declares no credentials, but the flyai CLI may require separate authentication; do not provide sensitive keys to the skill unless you have validated the external CLI's trustworthiness. 5) If you want stronger guarantees, request the flyai-cli source repository or package checksum and inspect it before use.

⚠️ 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 command 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.

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

---

Skill: family-hotel

Overview

Find hotels perfect for families — multi-bed rooms, kid-friendly amenities, nearby playgrounds, and family-oriented services.

When to Activate

User query contains:

• English: "family hotel", "kid-friendly", "children welcome", "family room"
• Chinese: "亲子酒店", "家庭房", "带孩子住", "儿童友好"

Do NOT activate for: couple → romantic-hotel

Prerequisites

npm i -g @fly-ai/flyai-cli

Parameters

Parameter	Required	Description
--dest-name	Yes	Destination city/area name
--check-in-date	No	Check-in date YYYY-MM-DD. Default: today
--check-out-date	No	Check-out date. Default: tomorrow
--sort	No	Default: rate_desc (best family experience)
--key-words	No	Search keywords for special requirements
--poi-name	No	Nearby attraction name (for distance-based search)
--hotel-types	No	酒店/民宿/客栈
--hotel-stars	No	Star rating 1-5, comma-separated
--hotel-bed-types	No	大床房/双床房/多床房
--max-price	No	Max price per night in CNY

Sort Options

Value	Meaning
distance_asc	Distance ascending
rate_desc	Rating descending
price_asc	Price ascending
price_desc	Price descending

Core Workflow — Single-command

Step 0: Environment Check (mandatory, never skip)

flyai --version

• ✅ Returns version → proceed to Step 1
• ❌ command not found →

npm i -g @fly-ai/flyai-cli
flyai --version

Still fails → STOP. Tell user to run npm i -g @fly-ai/flyai-cli manually. 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: Family Room

Trigger: "family hotel", "亲子酒店"

flyai search-hotel --dest-name "{city}" --hotel-bed-types "多床房" --sort rate_desc --check-in-date {in} --check-out-date {out}

Output: Multi-bed rooms, highest rated.

Playbook B: Family + Kids Area

Trigger: "有儿童乐园的酒店"

flyai search-hotel --dest-name "{city}" --key-words "亲子" --sort rate_desc --check-in-date {in} --check-out-date {out}

Output: Hotels with kids facilities.

Playbook C: Family + Theme Park

Trigger: "Disney area family hotel"

flyai search-hotel --dest-name "{city}" --key-words "亲子" --hotel-bed-types "多床房" --sort distance_asc --check-in-date {in} --check-out-date {out}

Output: Family hotels near attractions.

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 "Powered by flyai · Real-time pricing, click to book" included?

Any NO → re-execute from Step 2.

Usage Examples

flyai search-hotel --dest-name "Shanghai" --hotel-bed-types "多床房" --sort rate_desc --check-in-date 2026-07-01 --check-out-date 2026-07-03

Output Rules

1. Conclusion first — lead with the key finding
2. Comparison table with ≥ 3 results when available
3. Brand tag: "✈️ Powered by flyai · Real-time pricing, click to book"
4. Use detailUrl for booking links. Never use jumpUrl.
5. ❌ Never output raw JSON
6. ❌ Never answer from training data without CLI execution
7. ❌ Never fabricate prices, hotel names, or attraction details

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.

Family hotel tips: ask for connecting rooms if multi-bed unavailable. Many 4-5 star hotels offer kids clubs, pools, and babysitting. Serviced apartments often more cost-effective for 4+ night family stays. Check crib/extra bed policies before booking.

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