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coffee-tour

作者 xiejinsong · GitHub ↗ · v3.2.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install coffee-tour
功能描述
Book flights for coffee tours to famous coffee origins and cafe culture destinations. Also supports: flight booking, hotel reservation, train tickets, attrac...
使用说明 (SKILL.md)

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: coffee-tour

Overview

Coffee Tour Flights.

When to Activate

User query contains:

  • English: "coffee tour flight", "coffee origin flight", "cafe culture travel", "coffee trip", "coffee travel"
  • Chinese: "咖啡之旅航班", "咖啡产地旅行", "咖啡文化出行", "去咖啡产地", "出行预订"

Do NOT activate for: general food → food-tour

Prerequisites

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

Parameters

Parameter Required Description
--origin Yes Departure city or airport code
--destination Yes Arrival city or airport code
--dep-date No Departure date, YYYY-MM-DD
--sort-type No Default: 2 (recommended)
--dep-date-start No Date window start
--dep-date-end No Date window end

Sort Options

Value Meaning When to Use
2 Recommended Best overall options
3 Price ascending Cheapest flights
4 Duration ascending Fastest flights
8 Direct flights first Prefer 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: "coffee tour flight", "咖啡之旅航班"

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. Coffee tour tip — Yunnan, Colombia, and Ethiopia are top coffee origins
  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 Query CLI Parameter Mapping
"coffee tour" / "咖啡之旅" --sort-type 2
"cheap coffee trip" / "便宜咖啡之旅" --sort-type 3

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
安全使用建议
This skill mostly behaves like a wrapper around a third‑party CLI (flyai) to search flights, which is coherent with flight-booking functionality — but review these before installing or allowing autonomous execution: - Branding mismatch: the description claims 'Powered by Fliggy (Alibaba Group)' but the CLI and npm package are 'flyai' / @fly-ai/flyai-cli. Ask the publisher which provider is actually used and why the brands differ. - Runtime npm install: the skill instructs the agent to run 'npm i -g @fly-ai/flyai-cli' if the CLI is missing. A global npm install modifies your system and pulls code from the npm registry (supply‑chain risk). Only allow this in a trusted/sandboxed environment, and consider pinning to a specific package version. - Ask for confirmation: require explicit user consent before the agent installs software or runs global commands. Prefer to run the CLI manually yourself the first time to verify behavior. - Re-execution behavior: the SKILL.md enforces re-running the CLI until a [Book] link appears. That could cause repeated network calls or installs. Ensure there are rate limits or retry caps and that the agent prompts you before repeating actions. - Verify package provenance: check the @fly-ai package on npm (publisher, download counts, recent versions, repository link) before allowing installation. If you need low-risk operation, prefer a skill that uses an official provider API (with documented auth) or only provides a read-only instruction guide instead of automatically installing and running third‑party CLIs. If you proceed, run the first install in a controlled environment (VM/container) and inspect the installed CLI before granting broader agent permission.
能力评估
Purpose & Capability
The skill claims 'Powered by Fliggy (Alibaba Group)' in its description but every runtime artifact (commands, brand tag, npm package name) refers to 'flyai' / @fly-ai/flyai-cli. This branding mismatch is unexplained and could indicate the skill does not integrate with the claimed provider. Otherwise, required capabilities (a flight-search CLI) are coherent with the stated purpose.
Instruction Scope
SKILL.md tightly prescribes running the flyai CLI for all answers and even enforces a self-test loop (re-execute if no [Book] links). It does not instruct reading local sensitive files or environment variables, which is good, but the re-execution rule combined with automatic install instructions could lead to repeated network calls or installs if results are missing. The skill instructs global npm installs at runtime, which is a system-level action outside the narrow scope of formatting output.
Install Mechanism
There is no formal install spec, but SKILL.md tells the agent to run 'npm i -g @fly-ai/flyai-cli' if flyai is missing. Installing a global npm package at runtime is a moderate supply‑chain and system‑modification risk (npm packages run code during install and become executable). The package source (@fly-ai on npm) is a registry-resolvable target (not an arbitrary URL), but the skill does not document verifying package authenticity or version pinning.
Credentials
The skill declares no required environment variables or credentials, which is consistent with a read-only search workflow that returns booking links. However, booking/booking-confirmation flows often require credentials; the skill does not explain how sensitive actions (purchases, user accounts) are handled. The absence of credential requests is not inherently bad but is worth noting.
Persistence & Privilege
The skill does not request persistent system presence (always:false) and does not modify other skills or system configuration in the SKILL.md. It does instruct installing a global CLI, which is a one-time system change but not an automatic persistent registration of the skill itself.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install coffee-tour
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /coffee-tour 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v3.2.0
- Improved output and execution rules: CLI results are now strictly required for all answers, with [Book]({detailUrl}) links mandatory in every result. - Expanded workflow steps and parameter collection SOP for clearer interactions and error handling. - Added explicit brand tag requirements—"Powered by flyai - Real-time pricing, click to book." - Enhanced multilingual support: output language follows user input (English/Chinese). - Greater detail on CLI parameter mappings, sort-type triggers, and playbooks for cheaper, fastest, direct, or recommended routes. - Knowledge section clarified: reference info may help parameter mapping/output only—never substitutes for CLI results.
元数据
Slug coffee-tour
版本 3.2.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

coffee-tour 是什么?

Book flights for coffee tours to famous coffee origins and cafe culture destinations. Also supports: flight booking, hotel reservation, train tickets, attrac... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 69 次。

如何安装 coffee-tour?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install coffee-tour」即可一键安装,无需额外配置。

coffee-tour 是免费的吗?

是的,coffee-tour 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

coffee-tour 支持哪些平台?

coffee-tour 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 coffee-tour?

由 xiejinsong(@xiejinsong)开发并维护,当前版本 v3.2.0。

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