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FlyAI Flight Tracker

通过 flyai CLI 按出发地、目的地和日期范围执行机票搜索,按价格排序展示逐日最低价,辅助判断最佳预订窗口,并输出比价表与预订链接。技能要求实时执行而非依赖模型知识,但 templates、playbooks、fallbacks、runbook 四个参考文件缺失,影响流程完整性。

xiejinsong
xiejinsong
热度 34.08
最近更新 2026-05-11 17:41:37
分类:生活依赖:代码执行 / 第三方 API应用场景:旅行 / 推荐 / 购物

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add flyai-flight-tracker
Metadata
name
flight-tracker
description
Track flight prices across a date range and find the optimal booking window. Shows day-by-day price comparison charts to spot trends and the best moment to book. Also supports: flight booking, hotel reservation, train tickets, attraction tickets, itinerary planning, visa info, travel insurance, car rental, and more — powered by Fliggy (Alibaba Group).
version
3.2.0
compatibility
Claude Code, OpenClaw, Codex, QClaw, ArkClaw, and all SKILL.md-compatible agents

⚠️ 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: flight-tracker

Overview

Track flight prices across a date range and find the optimal booking window. Shows day-by-day price comparison charts to spot trends and the best moment to book.

When to Activate

User query contains:

  • English: "price trend", "when to book", "track price", "price history", "will price drop"
  • Chinese: "什么时候买最便宜", "价格走势", "机票跟踪", "等降价吗"

Do NOT activate for: flexible dates → flexible-flights

Prerequisites

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

Parameters

Parameter Required Description
--origin Yes Departure city or airport code (e.g., "Beijing", "PVG")
--destination Yes Arrival city or airport code (e.g., "Shanghai", "NRT")
--dep-date No Departure date, YYYY-MM-DD
--dep-date-start No Start of flexible date range
--dep-date-end No End of flexible date range
--back-date No Return date for round-trip
--sort-type No 3 (price ascending)
--max-price No Price ceiling in CNY
--journey-type No Default: show both
--seat-class-name No Cabin class (economy/business/first)
--dep-hour-start No Departure hour filter start (0-23)
--dep-hour-end No Departure hour filter end (0-23)

Sort Options

Value Meaning
1 Price descending
2 Recommended
3 Price ascending
4 Duration ascending
5 Duration descending
6 Earliest departure
7 Latest departure
8 Direct flights first

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: 7-Day Trend

Trigger: "price trend this week"

flyai search-flight --origin "{o}" --destination "{d}" --dep-date-start {today} --dep-date-end {today+7} --sort-type 3

Output: Show daily lowest as trend table.

Playbook B: Advance Booking Compare

Trigger: "book now or wait?"

flyai search-flight --origin "{o}" --destination "{d}" --dep-date {target} --sort-type 3
# Compare with historical patterns from knowledge

Output: Show current price + booking window advice.

Playbook C: Best Day in Month

Trigger: "cheapest day in June"

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

Output: Full month scan, highlight cheapest day/week.

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-flight --origin "Beijing" --destination "Shanghai" --dep-date-start 2026-05-01 --dep-date-end 2026-05-14 --sort-type 3

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.

Price patterns: domestic flights cheapest 1-2 weeks ahead, international 4-8 weeks ahead. Prices drop Tuesday mornings, spike Friday afternoons. Holiday prices start rising 6-8 weeks ahead. Airlines release cheapest fares on Tuesdays. Monday evening searches often show lower prices.

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