fix(skills): 补回 #56 压缩时误删的实质信息（意图对齐） (#57)

## 摘要 / Summary

### 中文

#56 的复盘修正。上一轮"强改写压缩"把四技能 L1
的**技术属性、使用场景与交互示范当套话一刀切**，造成实质信息丢失（承诺"意图全保留"但未做到）。本 PR 补回：

- **create**：`创建仓库符合 AgentFS v2 规范、git
管理版本（可治理/可追溯）`定位；`基础创建`形态（name+description，description 自动填充 persona
L0）；需求收集的**引导问题示例**（"起什么名字？/主要负责什么？"…）；企业部署/开发者原型使用场景。
- **update**：`agent 目录 git 管理版本、历史可追溯`定位 + 使用场景。
- **discover**：使用场景（浏览/新用户/找替代）+ `语义匹配而非关键词搜索`。
- **delete**：使用场景（清理/测试/释放存储）。

根因：L1 混着实质技术属性与营销套话、使用场景是触发判据、引导问题是交互示范，不该按"只留独有信息"一刀切。补回后仍保留结构性压缩（zh
正文合计仍降 ~64%）。版本 create 2.5.2 / update 3.1.3 / delete 2.5.2 / discover
2.6.2，manifest 1.2.13，中英双份同步、重算 source_hash（validate-i18n 通过）。

### English

Post-mortem fix for #56. The previous aggressive compression treated the
skills' L1 technical attributes, use cases, and interaction demos as
boilerplate and cut them in a blanket way, dropping substantive
information (the "all intent preserved" claim wasn't fully met). This PR
restores: create's AgentFS-v2 / git-version-management positioning, the
"basic create" form (name+description auto-filling persona L0), the
requirement-gathering prompt questions, and enterprise/developer use
cases; update's git-versioned/traceable positioning and use cases;
discover's use cases and "semantic match, not keyword search"; delete's
use cases. Root cause: L1 mixed real technical attributes with marketing
boilerplate, use cases are trigger cues, and prompt questions are
interaction demos — none should have been blanket-cut. Structural
compression is retained (zh bodies still ~64% smaller). Versions bumped,
manifest 1.2.13, both locales synced, source hashes recomputed
(validate-i18n passes).

skills/discover-agent/SKILL.md

@@ -1,7 +1,7 @@
 ---
 name: discover-agent
 description: 根据用户需求推荐最匹配的智能体，展示候选列表并引导选择。Use when 用户描述需求但不确定该找哪个智能体帮忙，或想浏览可用的智能体。
-version: 2.6.1
+version: 2.6.2
 type: procedural
 risk_level: low
 status: enabled
@@ -24,7 +24,7 @@ metadata:
       short_desc: 根据需求描述智能推荐最匹配的智能体，引导快速选择
       description: 根据用户需求推荐最匹配的智能体，展示候选列表并引导选择。Use when 用户描述需求但不确定该找哪个智能体帮忙，或想浏览可用的智能体。
       body: ./SKILL.zh-CN.md
-      source_hash: sha256:671b1b159567a5a3
+      source_hash: sha256:0a1c7b0b1b60e399
       translated_by: human
     en-US:
       name: Discover Agent
@@ -32,7 +32,7 @@ metadata:
       description: >-
         Recommend the best-matching Agent based on the user’s needs, show a candidate list, and guide selection. Use when the user describes a need but is unsure which Agent to ask for help, or wants to browse available Agents.
       body: ./SKILL.md
-      source_hash: sha256:671b1b159567a5a3
+      source_hash: sha256:0a1c7b0b1b60e399
       translated_by: ai:claude-fable-5
       translated_at: '2026-07-19'
 market:
@@ -64,7 +64,7 @@ Match and recommend the most suitable Agent among registered Agents based on the
 
 ## L1: Overview
 
-Procedural skill: understand the need → retrieve with `ManageAgent(action='list')` → semantic match scoring → rank and present → guide selection; on no match, hand off to create-agent automatically. Its value is what the tool can't give: semantic need matching, candidate ranking and presentation, and the create hand-off on no match. `list` / `get` are read-only, approval-free.
+Procedural skill: understand the need → retrieve with `ManageAgent(action='list')` → semantic match scoring → rank and present → guide selection; on no match, hand off to create-agent automatically. Applies when the user doesn't know which Agent to pick, wants to browse available Agents, is a new user getting oriented, or is unhappy with the current Agent and wants an alternative. Its value is what the tool can't give: semantic need matching (not keyword search), candidate ranking and presentation, and the create hand-off on no match. `list` / `get` are read-only, approval-free.
 
 ## L2: Detailed Spec