Pace Next

Community

arch-team

pace-next

Use when user asks "下一步做什么", "接下来做什么", "该做什么", "什么最重要", "应该先做哪个", "最紧急", "优先级", "推荐做什么", "为什么推荐这个", "pace-next", or wants a recommendation for the most important next action across all domains. NOT for current progress overview (use /pace-status).

Overview

Publisher	arch-team
Repository	`devpace`
Skill name	`pace-next`
Stars	73
Forks	6
Bundled files	6
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
6 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by arch-team on GitHub. Read the source before you install it.

Installation

Install the Pace Next AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/arch-team/devpace/tree/main/skills/pace-next
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/arch-team/devpace.git /tmp/devpace
mkdir -p .claude/skills
cp -r /tmp/devpace/skills/pace-next .claude/skills/pace-next

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pace Next in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Pace Next on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Pace Next is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

/pace-next — 下一步导航

跨域全局导航：综合 CR、迭代、Release、度量、风险、Epic/Opportunity 等多维信号，推荐当前最该做的 1 件事。

输入

$ARGUMENTS：

（空）→ 最高优先级 1 条建议（默认，≤ 3 行）
detail → 展开候选列表（≤ 8 行，含 top-3 建议）
why → 展开推理链（2-5 行，信号扫描 + 优先级对比 + 角色影响 + 备选）
journey [模板名] → 展示完整工作流路径：从当前状态到目标的分步引导
- 可选模板：new-feature（默认）、iteration、hotfix、release、onboarding
- 无模板名 → 根据当前项目状态自动选择最匹配的模板

执行路由

重要：根据 $ARGUMENTS 值，仅读取对应的输出规程文件，不加载全部规程。所有模式先加载 skills/pace-next/next-procedures.md（核心决策逻辑）。

参数	加载文件
（空）	`skills/pace-next/next-procedures.md` + `skills/pace-next/next-procedures-output-default.md`
`detail`	`skills/pace-next/next-procedures.md` + `skills/pace-next/next-procedures-output-detail.md`
`why`	`skills/pace-next/next-procedures.md` + `skills/pace-next/next-procedures-output-why.md`
`journey`	`skills/pace-next/next-procedures.md` + `skills/pace-next/next-procedures-journey.md`

流程

Step 1：检测项目状态

检查项目根目录是否存在 .devpace/state.md
不存在 → 输出未初始化引导（见 skills/pace-next/next-procedures.md），结束
存在 → 继续

Step 2：采集信号

读取 .devpace/ 下的数据源（目录/文件不存在时静默跳过）：

数据源	读取内容
`backlog/*.md`	CR 状态、类型
`state.md`	当前工作摘要
`releases/*.md`	Release 状态
`risks/*.md`	风险严重度
`iterations/current.md`	PF 完成率、周期
`metrics/dashboard.md`	最近更新日期
`project.md`	MoS、PF/BR/OBJ 映射
`integrations/sync-mapping.md`	同步状态（存在时）
`epics/*.md`	Epic 状态、BR 列表
`opportunities.md`	Opportunity 状态

提取关键状态字段（不全量读取）。额外采集 CR→PF→BR→Epic→OPP 价值链映射。

Step 3：优先级决策

从高到低遍历信号分组，取首个命中（判断细节见 skills/pace-next/next-procedures.md）：

组	信号
Blocking	S1 审批阻塞（in_review > 0）· S2 高风险阻塞（High 且 open）
In Progress	S3 继续开发（developing CR）· S4 恢复暂停（paused 阻塞解除）
Delivery	S5 Release 待验证 · S6 风险积压（open > 3）· S7 迭代紧迫（< 2 天且 < 50%）· S8 迭代接近完成（> 80%）
Strategic	S9 回顾提醒（> 7 天 + merged）· S10 缺陷占比（> 30%）· S11 同步滞后（> 24h）· S12 MoS 达成（> 80%）
Growth	S13 功能未开始 · S14 规划新迭代 · S15 全部完成 · S16 Epic 需分解 · S17 未评估机会 · S18 功能树稀疏 · S19 范围未定义 · S21 依赖阻塞 · S22 技术债积压 · S24 首次循环引导
Idle	S20 无信号

Step 3b：旅程路径生成（仅 journey 模式）

journey 模式跳过 Step 3 的信号优先级决策，改为按旅程模板生成分步路径。详见 skills/pace-next/next-procedures-journey.md。

Step 4：经验增强

匹配历史经验 pattern（.devpace/metrics/insights.md，如存在），在建议中附加 ≤1 行经验参考。

Step 5：角色适配

根据当前角色（Dev/PM/Biz/Tester/Ops）调整建议措辞维度和信号组内排序。

Step 6：输出

按路由表加载的输出规程文件格式化输出。

输出

≤ 3 行（默认）或 ≤ 8 行（detail）或 2-5 行推理链（why）。自然语言为主，不暴露 ID。建议体现价值链上下文。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Pace Next AI skill do?

Why use Pace Next on TypingMind?

Because you install it once and use it with any model. Pace Next is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Pace Next in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/arch-team/devpace/tree/main/skills/pace-next. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Pace Next?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Pace Next?

As many as you like. As long as a model supports skills, you can use Pace Next with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Pace Next AI skill free?

Yes. It is published on GitHub by arch-team under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

/pace-next — 下一步导航

输入

执行路由

流程

Step 1：检测项目状态

Step 2：采集信号

Step 3：优先级决策

Step 3b：旅程路径生成（仅 journey 模式）

Step 4：经验增强

Step 5：角色适配

Step 6：输出

输出

Bundled files

Frequently asked questions

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