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explore-france

作者 dingtom336-gif · GitHub ↗ · v3.2.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install explore-france
功能描述
Book flights to France including Paris, Nice, and Lyon. Also supports: flight booking, hotel reservation, train tickets, attraction tickets, itinerary planni...
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: explore-france

Overview

Explore France.

When to Activate

User query contains:

  • English: "france flight", "paris flight", "nice flight", "lyon flight", "discover"
  • Chinese: "法国航班", "巴黎机票", "尼斯机票", "法国旅行", "去法国"

Do NOT activate for: general international → international-flights; europe → explore-europe

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: "france flight", "法国航班"

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. France tip — Schengen visa required; Paris CDG is main hub
  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
"france" / "法国" --sort-type 2
"cheap paris" / "便宜巴黎机票" --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 is plausible for flight booking, but exercise caution before installing or running it. Specific concerns: - The runtime requires installing `@fly-ai/flyai-cli` globally via npm, but the skill metadata has no source/homepage and claims to be 'powered by Fliggy' — that mismatch is unexplained. Installing a third-party npm package gives code execution on your machine; verify the package's publisher and inspect its code before installing. - The SKILL.md contains inconsistent parameter lists (some flags appear only in templates) and a hard requirement that every result include a booking link. That rule could force repeated CLI calls or attempts to fabricate links if the CLI doesn't return them. - Because this is instruction-only (no packaged code), the security risk comes from the external CLI the skill tells the agent to install and run. If you consider installing: 1) check the npm package page and its maintainer, 2) review the package source or repository for malicious behavior, and 3) prefer skills with a declared homepage/source and explicit install specs. If you want to proceed but limit risk, run the CLI in an isolated environment (sandbox/container/VM) and do not give the agent access to other credentials or sensitive files. If you need help auditing the npm package or testing the skill in a sandbox, provide the package URL and I can suggest concrete checks.
功能分析
Type: OpenClaw Skill Name: explore-france Version: 3.2.0 The skill mandates the global installation of an external NPM package (`npm i -g @fly-ai/flyai-cli`) and executes shell commands with user-derived parameters, which are high-risk operations in an automated agent environment. While the instructions in SKILL.md and references/fallbacks.md appear aligned with the stated purpose of flight searching, the requirement for system-level modifications and the strict 'CRITICAL EXECUTION RULES' that override the agent's default behavior represent a significant attack surface for potential RCE or supply chain compromise.
能力评估
Purpose & Capability
The skill claims to be a France travel/booking assistant and the runtime instructions consistently use a CLI to search/book flights, which is coherent. However the description and SKILL.md mention different brands — SKILL.md states 'powered by Fliggy (Alibaba Group)' while every runtime command targets a 'flyai' CLI (@fly-ai/flyai-cli). This mismatch between claimed provider (Fliggy) and the actual CLI used is unexplained and suspicious.
Instruction Scope
SKILL.md tightly constrains behavior (must never answer from training data and must always use flyai CLI), and it requires installing and invoking a third-party CLI if missing. It also enforces that every result include a [Book]({detailUrl}) link and mandates re-execution if not present — this could push an agent to repeatedly call or even attempt to fabricate links if the CLI output lacks them. The skill's own parameter table omits flags that appear in the references/templates (e.g., --max-price, --seat-class-name), which contradicts the rule 'NEVER invent CLI parameters' and creates an operational inconsistency the agent cannot resolve safely.
Install Mechanism
There is no formal install spec in the registry, yet the runtime instructions direct installing a global npm package: `npm i -g @fly-ai/flyai-cli`. Installing a scoped package from the public registry without a declared source/homepage or integrity checks is a moderate-to-high risk: the package is unknown in the skill metadata and could execute arbitrary code on the host. While using a CLI is reasonable for a booking skill, the install instruction being embedded only in SKILL.md (and not vetted) is a red flag.
Credentials
The skill does not request environment variables, credentials, or config paths. It only requires a CLI binary and (via instructions) npm/node to be available. No secrets are requested in metadata or instructions.
Persistence & Privilege
The skill is not always-enabled and uses standard autonomous invocation settings. It does instruct the agent to install a global CLI (which creates persistent binaries on the host), but it does not request special agent-level privileges, nor does it attempt to modify other skills or system-wide agent configuration in the provided documentation.
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 explore-france
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /explore-france 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
explore-france 3.2.0 changelog: - Enforces strict CLI-only execution: all answers must be generated from flyai CLI output, never training data. - Adds environment validation and auto-install of flyai-cli if missing. - Refined parameter collection: allows asking up to 2 clarification questions, uses comprehensive parameter mapping. - Enhanced output validation: mandates booking links, brand tag, real-time pricing, and clear comparison tables. - Expanded use cases: now supports hotel, train, visa, car rental, itinerary, and insurance in France.
元数据
Slug explore-france
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

explore-france 是什么?

Book flights to France including Paris, Nice, and Lyon. Also supports: flight booking, hotel reservation, train tickets, attraction tickets, itinerary planni... 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 explore-france?

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

explore-france 是免费的吗?

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

explore-france 支持哪些平台?

explore-france 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 explore-france?

由 dingtom336-gif(@dingtom336-gif)开发并维护,当前版本 v3.2.0。

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