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fix(skills): 去除束缚 Agent 自主判断的机械数字策略 (#58)
## 摘要 / Summary ### 中文 去除技能里束缚执行 Agent 自主判断的**机械数字策略**:create 需求收集的「每轮最多问 2 个」、discover 排序的「最多展示 5 个候选」。改为交由 Agent 按情况自主把握追问节奏与展示数量,保留「别让用户负担 / 别一次刷屏」的原则意图——把控制权交还给判断力更强的执行者,而非用固定上限约束。create 2.5.3 / discover 2.6.3,manifest 1.2.14,中英双份同步、重算 source_hash(validate-i18n 通过)。 ### English Remove mechanical numeric limits that constrain the executing Agent's judgment: create's "at most 2 questions per turn" and discover's "show at most 5 candidates". Both become "the Agent decides the pacing/count by situation", keeping the principle intent (don't burden the user / don't flood the screen) while handing control back to the more capable executor instead of a fixed cap. create 2.5.3 / discover 2.6.3, manifest 1.2.14, both locales synced, hashes recomputed (validate-i18n passes).
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# Changelog
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## [2.5.3] - 2026-07-19
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- 去除束缚执行 Agent 自主判断的机械数字策略(create 追问'每轮最多 2 个'、discover'最多展示 5 个候选'),改为交由 Agent 按情况自主把握节奏与数量,保留'别让用户负担/别刷屏'的原则意图。
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## [2.5.2] - 2026-07-19
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- 复盘补回改写压缩时误删的实质信息:create 的 AgentFS v2/git 版本管理定位、基础创建(name+description 自动填充 persona L0)、需求收集引导问题示例;update/delete/discover 的使用场景与版本管理定位。功能对齐原始意图,仍保留结构性压缩。
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name: create-agent
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description: >-
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通过多轮对话收集需求,调用 ManageAgent 内置工具创建新的 AgentFS v2 智能体,支持自定义 persona 和 principles。Use when 用户要求创建新智能体、培养某领域助手、或快速基于模板生成可治理 Agent。
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version: 2.5.2
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version: 2.5.3
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type: meta
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risk_level: low
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status: enabled
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@@ -26,7 +26,7 @@ metadata:
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description: >-
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通过多轮对话收集需求,调用 ManageAgent 内置工具创建新的 AgentFS v2 智能体,支持自定义 persona 和 principles。Use when 用户要求创建新智能体、培养某领域助手、或快速基于模板生成可治理 Agent。
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body: ./SKILL.zh-CN.md
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source_hash: sha256:fa447cd4d5a5b336
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source_hash: sha256:72090265f12a8da0
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translated_by: human
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en-US:
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name: Create Agent
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@@ -34,7 +34,7 @@ metadata:
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description: >-
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Collect requirements through multi-turn conversation and call the ManageAgent builtin tool to create a new AgentFS v2 Agent, with customizable persona and principles. Use when the user asks to create a new Agent, raise a domain assistant, or quickly produce a governable Agent from a template.
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body: ./SKILL.md
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source_hash: sha256:fa447cd4d5a5b336
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source_hash: sha256:72090265f12a8da0
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translated_by: ai:claude-fable-5
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translated_at: '2026-07-19'
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market:
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@@ -82,7 +82,7 @@ Trigger (any): user explicitly says "create an Agent / make me an assistant"; de
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- Required (parenthesized = example prompt question): `name` ("what to name it?"), `role` ("what does it mainly do?"), `target_users` ("who will use it?"), `domain` ("what expertise does it need?").
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- Optional: `style` (communication tone), `boundaries` (red lines), `language` (default Chinese) — defaults derived from the domain template.
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- Strategy: prefer inferring from the user's natural description; only ask for missing required fields; at most 2 questions per turn.
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- Strategy: prefer inferring from the user's natural description; only ask for missing required fields; you decide how many to ask and the pacing — don't ask too many at once so as not to burden the user.
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### Stage 3: Content Generation
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@@ -22,7 +22,7 @@
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- 必填(括号内为引导问题示例):`name`("起什么名字?")、`role`("主要负责什么工作?")、`target_users`("谁会使用它?")、`domain`("需要哪些专业知识?")。
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- 选填:`style`(沟通风格)、`boundaries`(禁区/红线)、`language`(默认中文)——缺省由领域模板决定。
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- 策略:优先从用户自然描述推断,只追问未提及的必填项,每轮最多问 2 个。
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- 策略:优先从用户自然描述推断,只追问未提及的必填项;追问的数量与节奏由你自主把握,一次不要问太多以免用户负担。
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### 阶段 3:内容生成
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