能不能像Anthropic那样给飞书的产品系列做一个<路由指南>Skill

Feature Request: 为飞书产品系列做一个「路由」Skill

背景

现在 lark-cli、lark-skills、飞书开发平台文档都做得非常成熟了。但在实际使用中，Agent 回答飞书相关问题时，经常需要在 prompt 中手动注入「请基于飞书官方文档作答」——既重复麻烦，又容易错误地定位文档。

如果能内置一个路由 Skill，让 Agent 在回答时自动匹配正确的文档源，准确率会不会更高？

参考：Anthropic 的 product-self-knowledge Skill

Anthropic 为自家产品（Claude Code / Claude API / Claude.ai）做了一个路由 Skill，效果很好。核心思路是：

当 Agent 的回答涉及产品相关事实时，先查路由表定位到正确的文档，再基于文档作答，而不是凭记忆猜测。

以下是其 Skill 的完整结构，供参考：

<details> <summary>📄 Anthropic product-self-knowledge Skill 完整内容</summary>

---
name: product-self-knowledge
description: >
  Stop and consult this skill whenever your response would include specific facts
  about Anthropic's products. Covers: Claude Code (how to install, Node.js requirements,
  platform/OS support, MCP server integration, configuration), Claude API (function calling/tool use,
  batch processing, SDK usage, rate limits, pricing, models, streaming), and Claude.ai
  (Pro vs Team vs Enterprise plans, feature limits). Trigger this even for coding tasks
  that use the Anthropic SDK, content creation mentioning Claude capabilities or pricing,
  or LLM provider comparisons. Any time you would otherwise rely on memory for Anthropic
  product details, verify here instead — your training data may be outdated or wrong.
---

Core Principles

1. Accuracy over guessing — Check official docs when uncertain
2. Distinguish products — Claude.ai, Claude Code, and Claude API are separate products
3. Source everything — Always include official documentation URLs
4. Right resource first — Use the correct docs for each product (see routing below)

Question Routing

问题类型	路由目标
Claude API / General	https://docs.claude.com/en/docs_site_map.md
Claude Code	https://docs.anthropic.com/en/docs/claude-code/claude_code_docs_map.md
Claude.ai	https://support.claude.com

预期收益

• 减少重复 prompt 注入 — 不再需要每次手动提示「请基于官方文档」
• 提高回答准确率 — Agent 先定位文档再作答，减少幻觉
• 降低文档错配 — 路由表明确区分不同产品线的文档源
• 对齐行业最佳实践 — Anthropic 已验证此模式有效

Start by reviewing the existing lark-cli and lark-skills structures, the Feishu developer documentation, and Anthropic’s product-self-knowledge example and routing URLs. Define the Feishu product categories and their official documentation sources, then verify that the resulting Skill routes product questions to the appropriate source without relying on memory.