Comet Native logo

Comet Native

OrganizationPopular
rpamis
comet-native

Comet Native 工作流。当用户明确调用 /comet-native、要求启动或恢复 Native change,或入口路由到 Native 时使用。

Overview

Publisherrpamis
Repositorycomet
Skill namecomet-native
Stars
3.1K
Forks
295
Bundled files
6
LicenseMIT
Links
  • 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 rpamis on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. 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.
2

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/rpamis/comet.git /tmp/comet
mkdir -p .claude/skills
cp -r /tmp/comet/assets/skills-zh/comet-native .claude/skills/comet-native
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Comet Native 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 Comet Native 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 Comet Native 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.

Comet Native

Native 将完整需求、进度和验收结论保存在项目中。Agent 只处理 Runtime 指定的当前阶段。完成当前动作后,读取最新 continuation 并按其中的指令继续,直到任务完成、需要用户决定,或遇到外部阻塞。

必须遵守的规则

  • 以磁盘上的 .comet/config.yaml、当前 change、comet-state.yaml 和正式文件为准,聊天记忆只作辅助。工作流保存的正式文件中,Agent 只编辑 brief、完整目标 Spec 和 children.yaml;状态、检查结果、报告、锁和事务由 Runtime 管理。
  • 通过 PATH 中公开的 comet native 命令推进,用户不手工执行命令。命令不可用时报告安装不完整并停止;参数以 comet native <command> --help 为准。
  • Builder 提交本轮待验收的代码和相关文件,称为“候选实现”。每轮都由新的只读 Verifier 独立判断全部验收项。失败、阻塞、未执行和超时不能算通过。
  • 只有用户明确确认完整 Shape、接受最终结果或选择相应交付方式后,才执行对应的确认命令。沿用已确认的需求范围和 Runtime 保存的用户选择。归档、merge、push、PR 和工作区清理各自需要的授权不能互相代替。
  • Native 主流程由本 Skill 和 Runtime 完成,不依赖外部 Skill;不改变已确认的需求和约束时,实现方法由 Agent 自行选择。

开始或恢复

  1. 已知名称时运行 comet native status <change-name> --json;未知时先运行 comet native status --json 确定目标。
  2. active change 已存在时,进入返回的 workspace.projectRoot 并执行 select。由 Runtime 查找工作区;只有多个工作区同样匹配时,才让用户选择。
  3. 没有对应 active change 时,按工作区选择参考确定隔离方式并创建,再进入 preparation.projectRoot。准备失败时,保留已创建的分支和目录,按返回的原因处理。
  4. 进入工作区并取得 phase 后,按记忆接入检索一次上下文。需要详情时再展开;实际使用后记录使用结果,任务结束时调用 comet task --complete。具体操作见该节。

记忆学习只提交可复用的用户信息;任务摘要、进展、命令输出和测试结果不写入个人记忆。任务结束前按记忆接入章节完成学习检查,并记录 submittedno-observationnot-run

按需读取

只读取当前动作对应的章节。章节中的链接写明了适用条件,满足条件时再读取链接内容;不一次加载整份命令参考或所有参考。

  • Shape:必须读取并执行澄清,按项目配置选择 Sequential 或 Batch 的提问步骤。大型需求在最终确认前,必须按该节链接读取 Supervisor 拆分与确认要求。
  • 编辑 brief/Spec/children.yaml 或核对验收报告前,必须读取正式产物。文件、附件、链接或本地路径作为需求来源时,必须进入源文档完整覆盖模式;仅用于排错、取证、审查或实现参考的材料不自动触发。
  • 首次填写 Runtime 模板或通过 returnAction 回传结果前,必须读取填写命令输入
  • Builder 提交本轮实现前,必须读取Builder 交接。启动 Verifier、补充检查或等待结果前,必须读取Verify 协议
  • 状态包含 childSummary 时,必须在分配任务、接收结果或集成前读取Supervisor 协作,只处理 readyChildren 列出的子任务和 Supervisor 统筹动作。
  • 字段含义不清、命令输入被拒绝、Verifier 不可用、执行错误或缺少外部信息:读取命令输入与异常。正常动作直接使用 Runtime 返回的命令和模板。
  • 等待外部输入时,按恢复参考中的等待外部输入与监控处理;独立工作继续。进程中断、换设备、连续无进展、并发冲突、迁移失败或状态损坏时,读取故障恢复

Shape

Agent 先调查能够查明的事实,只询问会改变用户可见结果、又无法可靠推断的决定。简单问题列出未决项及其依赖关系;多个决定相互影响时才建立决策树。按 native.clarification_mode 提问前,先把本轮尚未解决的问题写入 brief。用户确认的结论立即同步到 Decisions、brief 和完整目标规格;未明确回答的部分保持 [blocking]

完成标准:需求来源已按用途完整覆盖,所有影响结果的决定和假设已处理,没有 [blocking],用户明确确认目标、范围、关键决定、全部验收项和非目标,并且 Runtime 已进入 Build。

Build ↔ Verify Loop

Builder 提交候选实现后,由 Runtime 执行必要检查,再交给新的只读 Verifier 验收。未通过则回 Build 修复并重新提交;全部通过后,等待用户接受验收结果。

iteration 表示提交实现的轮次,attempt 表示对同一份候选实现启动 Verifier 的次数。所有计数都由 Runtime 更新。连续验收失败或没有进展的次数达到配置上限时,按最新指令等待用户决定或处理阻塞。

Build

首次实现前,读取当前 brief、完整目标规格和全部验收项,在已确认的需求范围内修改项目代码和测试。修复时优先处理 Verifier 指出的未通过项、无法验证的原因和失败检查;提交前仍要核对其他已确认行为。previous_unresolved_ids 只提示本轮修复重点,下一次正式验收仍覆盖全部验收项。

需求变化时,先判断变化属于哪种情况,再执行当前 continuation 允许的动作:

  • 已确认的功能有实现遗漏:从 Verify 使用 --revise-implementation,保留已确认的需求范围,回 Build 修改。
  • 用户可见行为或验收标准发生变化:从 Verify 或 Archive-ready 使用 --revise-requirements,更新正式文件并重新确认 Shape。
  • 与当前需求无关:交给另一个 change。

用户明确补充当前范围时,按同一规则处理。

用户确认一次 Supervisor Shape,就授权执行该范围内的全部子任务。按 Runtime 的指令分配和集成子任务,随后自动进行 Supervisor 主任务的最终验收,覆盖全部验收项。按Supervisor 协作区分统筹、Builder 和 Verifier 的职责;只有 Runtime 接受了子任务的验收结果并确认集成成功,才算完成。

完成标准:实现和相关检查可供验收,Runtime 接受 Builder 交接并进入 Verify。

Verify

按 Verify 协议立即启动独立的只读 Verifier。Verifier 核对检查记录是否对应当前实现版本、工作区和输入,只补充缺失或失效的检查,并独立判断全部验收项。Builder 交接时,只传本轮实现的位置、验收项的编号与引用、检查记录位置、已知限制和相关文件位置;日志正文按需读取。

等待工具超时后,继续等待同一个 Verifier。只有平台确认执行失败、执行超时、任务丢失或结束后没有可用结果时,才登记错误。Runtime 接受完整结果后,按最新状态继续。需要用户接受最终结果时,只有用户明确接受,才执行 --accept-result;仅完成自动检查、没有独立验收的结果也须由用户明确接受。

完成标准:Runtime 接受每项验收结论并给出下一步;返回 Build 就继续修复,返回等待或阻塞就处理对应条件,不把阶段结束当任务完成。

Archive

continuation 允许 Archive 时,必须先读Archive 收尾,使用已接受的验收结果,执行 Runtime 返回的完整 archive --dry-run。只处理同一响应列出的阻塞;ready: true 后才执行返回的唯一 archive --confirmed 命令。

只提交本 change 的实现和正式产物,保留无关修改。检查 workspaceFinishResult,阻塞时按 recoveryArgs 保留现场并恢复。

完成标准:状态为 done,用户授权的工作区收尾为 completedkept,并按记忆接入协议记录任务完成;其他结果继续处理。

后续指令

  • continue:在返回的工作目录执行完整 commandArgs,按 inputOptions 模板填写输入。
  • await-user:先转述 userCommunication.messagesuggestedReply,等待列出的决定;按用户选择执行 commandAlternatives,保留 --expected-state-version--expected-action。过期时读取最新状态,不自行拼接无保护命令。
  • blocked:处理列出的阻塞或恢复动作;仅暂停依赖该条件的工作。
  • done:核对 Archive 完成标准后结束。

命令成功且响应包含 agent 时,直接使用其中的阶段、状态版本、workspace.cwdcontinuation 继续。只在字段缺失、命令被拒绝或需要额外正文时读取详情;恢复会话、响应缺失或有外部变化迹象时,才重新查询 status。不因等待工具超时重复派发已有的 Verifier 或子任务。

当前动作需要验收文字、交接摘要或历史详情时,才加 --details,并按 nextPageArgs 读取 scopeIds 涉及的全部页面。需要正式文件的正文时,才运行 show。阅读 CLI 文本时,先看 summary、唯一的 NEXT: 和可选转述消息;程序解析使用 --json,排查本机执行状态时才用 --verbose

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 Comet Native AI skill do?

Comet Native 工作流。当用户明确调用 /comet-native、要求启动或恢复 Native change,或入口路由到 Native 时使用。

Why use Comet Native on TypingMind?

Because you install it once and use it with any model. Comet Native 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 Comet Native in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rpamis/comet/tree/master/assets/skills-zh/comet-native. 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 Comet Native?

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 Comet Native?

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

Is the Comet Native AI skill free?

Yes. It is published on GitHub by rpamis 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇