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garden-parks

作者 xiejinsong · GitHub ↗ · vv3.2.2 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install garden-parks
功能描述
Explore classical Chinese gardens, city parks, botanical gardens, and royal gardens — perfect for relaxing walks and cultural appreciation. Also supports: fl...
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 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: garden-parks

Overview

Explore classical Chinese gardens, city parks, botanical gardens, and royal gardens — perfect for relaxing walks and cultural appreciation.

When to Activate

User query contains:

  • English: "garden", "park", "botanical", "flowers"
  • Chinese: "园林", "公园", "花园", "植物园"

Do NOT activate for: nature → nature-spots

Prerequisites

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

Parameters

Parameter Required Description
--city-name Yes City name
--keyword No Attraction name or keyword
--poi-level No Rating 1-5 (5 = top tier)
--category No --category "园林花园"

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: Gardens

Trigger: "gardens to visit"

flyai search-poi --city-name "{city}" --category "园林花园"

Output: Gardens and parks.

Playbook B: Classical Gardens

Trigger: "Chinese garden"

flyai search-poi --city-name "{city}" --category "园林花园" --poi-level 5

Output: Top classical gardens.

Playbook C: Botanical Gardens

Trigger: "botanical garden"

flyai search-poi --city-name "{city}" --category "植物园"

Output: Botanical gardens.

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-poi --city-name "Suzhou" --category "园林花园"

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.

China's classical gardens: Suzhou (9 UNESCO gardens), Beijing (Summer Palace, Temple of Heaven Park), Hangzhou (West Lake gardens). Suzhou gardens are best in spring (plum blossom) and autumn (chrysanthemum). Mornings less crowded. Some gardens host night shows with lighting.

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 appears coherent for discovering gardens and parks via the flyai CLI. Before installing or allowing it to run, consider: 1) Verify the @fly-ai/flyai-cli npm package source and reputation (global npm installs run code on your machine). 2) The skill will try to run npm i -g @fly-ai/flyai-cli if the CLI is absent — be sure you want that action. 3) The references include an optional local execution log (.flyai-execution-log.json) which could store user queries/results; if you don't want local logs, block or inspect that behavior. 4) No credentials are requested by the skill, and it requires network access to contact flyai; if you trust the flyai service and the npm package, the skill is consistent with its stated purpose.
功能分析
Type: OpenClaw Skill Name: garden-parks Version: v3.2.2 The skill instructions in SKILL.md and references/fallbacks.md mandate the automated global installation of an external NPM package (@fly-ai/flyai-cli) using 'npm i -g' if the command is not found. While this is aligned with the stated purpose of providing travel data via the FlyAI CLI, instructing an AI agent to perform global software installations without explicit user intervention is a high-risk behavior that could be leveraged for supply chain attacks or unauthorized system modifications.
能力评估
Purpose & Capability
The name/description claim travel/park discovery and booking; SKILL.md consistently requires the flyai CLI and only runs flyai search-poi / keyword-search commands. Requiring the flyai CLI is proportionate to the stated functionality.
Instruction Scope
Instructions are narrowly scoped to running flyai CLI commands, collecting parameters, formatting results, and enforcing that outputs include [Book]({detailUrl}) links. A notable artifact in the references (runbook.md) suggests appending an execution log to .flyai-execution-log.json if filesystem writes are available — this is not necessary to fulfill queries but is present in the skill docs and can cause local writes.
Install Mechanism
The skill is instruction-only (no install spec). It instructs the agent/user to run npm i -g @fly-ai/flyai-cli if flyai is missing. Using a published npm package is normal for this purpose, but the skill does not include a declared homepage/source in metadata; users should verify the @fly-ai package provenance before installing globally.
Credentials
The skill declares no required environment variables, no credentials, and no config paths. The runtime instructions do not request secrets or unrelated credentials.
Persistence & Privilege
The skill is not always-included and does not request elevated privileges. The only persistence-related behavior is an optional runbook suggestion to append an execution log file (.flyai-execution-log.json) to the working directory; this is local and limited but should be considered by users who want no logs written.
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 garden-parks
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /garden-parks 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
vv3.2.2
v3.2.2 Changelog - No code or documentation changes detected in this version. - Version number bump only; functionality and rules remain unchanged.
vv3.2.1
- No code or configuration changes in this version. - All files remain unchanged from the previous release. - Version bump only; behavior and features are identical to v3.2.0.
v3.2.0
garden-parks v3.2.0 - Enforces strict CLI-only data source: Never answers from training data; all responses must use flyai CLI output. - Adds critical execution rules, self-test checks, and output validation steps to ensure data provenance. - Updates parameter usage, activation keywords, and CLI playbooks for garden-related travel queries. - Output and formatting rules clarified: must have booking links, brand tag, and user-friendly summaries. - Expanded description and compatibility details in SKILL.md.
元数据
Slug garden-parks
版本 v3.2.2
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 3
常见问题

garden-parks 是什么?

Explore classical Chinese gardens, city parks, botanical gardens, and royal gardens — perfect for relaxing walks and cultural appreciation. Also supports: fl... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 77 次。

如何安装 garden-parks?

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

garden-parks 是免费的吗?

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

garden-parks 支持哪些平台?

garden-parks 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 garden-parks?

由 xiejinsong(@xiejinsong)开发并维护,当前版本 vv3.2.2。

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