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agent-draft-router

Generate checklist-first CodexBridge `/agent` drafts from natural-language intake using bounded action routing, skill-owned task typing, scope clarification, and immutable prompt scaffolds. Use when implementing, testing, or simulating first-host `/agent add` or bare `/agent` draft creation, especially for repo-aware `code` missions and lighter generic non-code missions.

DeepseekModel 官方收录技能 质量 优秀 · 78 v1.0.0

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https://deepseekmodel.com/api/download.php?id=gan-xing-codexbridge-skills-agent-draft-router-skill-md&format=skill
下载 .skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
name agent-draft-router description Generate checklist-first CodexBridge `/agent` drafts from natural-language intake using bounded action routing, skill-owned task typing, scope clarification, and immutable prompt scaffolds. Use when implementing, testing, or simulating first-host `/agent add` or bare `/agent` draft creation, especially for repo-aware `code` missions and lighter generic non-code missions. Agent Draft Router Use this skill only for first-host /agent draft intake. Do not use it for: explicit /agent confirm|edit|cancel|list|show|result|stop|retry|delete|rename|send Mission runtime execution package-owned lifecycle control Primary reference: ../../docs/architecture/agent-draft-templates.md Read that document when you need the full code or generic template contract. Workflow Determine whether the request is draft intake at all. Keep explicit /agent subcommands deterministic and out of model routing. For bare /agent <text> or /agent add <text> , emit only a bounded action. If the action is add/create, enter create-flow: determine task type inside the skill clarify only when the missing information is truly blocking generate the formal checklist generate the immutable prompt generate loop policy Produce a checklist-first draft rather than a generic lifecycle plan. Routing Rules Allowed bounded actions for natural-language intake: create_draft update_pending_draft clarify query_jobs show_job show_result propose_stop propose_retry reject Prefer clarification over forced routing when confidence is low. Do not: invent jobs or drafts mutate authoritative mission state bypass deterministic bridge handlers bypass package-owned approval or change gates Create-Flow Rules Only continue into create-flow when the action clearly resolves to add/create. Inside create-flow: Determine task type from the current request and repo context. If the task is genuinely ambiguous or underspecified, ask one narrowing question. Generate a formal checklist, not a generic software lifecycle. Generate an immutable prompt scaffold that can survive autonomous loops. Keep internal substeps separate from formal checklist mutation. code Missions For code missions, prefer: repo-aware checklist items fixed immutable prompt scaffolding explicit verification commands explicit execution boundaries bilingual Conventional Commit requirements when repository changes are in scope repo context from the invocation payload over fixed path assumptions distill the user input into one direct sentence with at most one comma; do not expand it into rationale, checklist, or scope narration generate plan[] from the user goal plus repo context, and never leave it empty if at least 3 concrete checklist items cannot be derived from the goal and context, return clarify instead of forcing create_draft Do not fall back to: analyze design code test deploy unless those are truly the correct bounded checklist items. Generic Non-Code Missions For generic non-code missions: keep the prompt lighter than code still require immutable goal, checklist, acceptance criteria, and loop policy still require checklist/progress updates each cycle State-Aware Loop Expectations When shaping immutable prompts, make sure the loop can use Mission Control status semantics: running / verifying / repairing : take the smallest next executable step waiting_user : ask one concrete blocking question needs_human : summarize why autonomy is no longer reasonable handoff : preserve current state and recommended next owner action blocked : describe the blocker precisely and offer options max_loops_reached : explain which budget was exhausted and the next recovery path To avoid "do two steps then stall" behavior: prefer one bounded next step over broad re-planning prefer checklist refinement suggestions over vague failure language only clarify when the missing information is truly blocking Output Requirements When generating or updating drafts: treat plan[] as the formal confirmed checklist / TODO preserve user-confirmed scope unless a formal refinement is required ensure the immutable prompt explicitly requires checklist-status updates, overall progress updates, blockers, and next-step updates each cycle for code missions, include bilingual Conventional Commit rules whenever repository changes are allowed When editing a draft: return the full updated draft, not a patch preserve fields the user did not request to change
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下载的 .skill 包内含以下字段。
字段 说明
format格式标识(skill/v1)
skill_id技能唯一 ID
name技能名称
version版本号
description技能描述
category所属分类(数组)
trigger_words触发词列表
tags标签列表
source来源标识
source_url来源链接(本页地址)
exported_at导出时间(每次下载生成)
system_prompt系统提示词正文
model_config模型参数:provider / model / temperature / max_tokens / top_p
examples示例
install_guide各平台导入说明(Coze / Dify / Claude / 自定义框架)
同一份技能可按不同平台格式导出。
.skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用 下载
.skillpro 增强格式,额外含脚本 / 工具 / 依赖 / 钩子占位 下载
.json 纯 JSON 导出,只含 system_prompt 与模型参数 下载
Coze 带 frontmatter 的 Markdown,Coze 平台导入用 下载
Dify Dify DSL,创建应用后直接导入 下载

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