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Comet Any

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rpamis
comet-any

通过 Comet Creator 创建或升级 Comet Classic workflow Skill。不用于一般 Skill 的编写、整理或评审。

Overview

Publisherrpamis
Repositorycomet
Skill namecomet-any
Stars
3.1K
Forks
295
Bundled files
12
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.

  • 12 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 Any 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-any .claude/skills/comet-any
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Comet Any 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 Any 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 Any 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 Any - Skill Creator

/comet-any 是 Comet 的 Skill 创建向导。用户只需要描述想要的工作流;本 Skill 负责读取真实 Skill、提出方案、等待确认、生成可验证的 Comet-native Skill Bundle,并通过内部 CLI 完成 eval、review、publish readiness 和安装预览。

普通用户第一层只看到三种起点:

  • 基于 /comet-classic 的五阶段定制:覆盖 open / design / build / verify / archive 五阶段的 Skill 编排,但不修改 /comet-classic 永久入口本身。
  • 创建全新 workflow Skill:从目标和候选 Skills 生成新的 workflow-kernel
  • 整理已有 Skill:读取已有 Skill,补齐 Workflow Node、Skill Binding、Output Schema、Guardrail、Handoff、eval 和 readiness。

后端 Bundle、Factory、composition 仍是内部审计词;不要把它们作为普通用户的第一屏概念。

核心模型

所有路径都必须编译到同一种 Workflow Contract:

  • Workflow Node:流程中的可恢复节点,例如 opendesignplanexecutesubagent-executereviewverifyarchive
  • Node Responsibility:该 Node 在 Agent workflow 中承担的职责,用来解释它为什么存在、需要产出什么、能否替换。
  • Skill Binding:某个 Node 的实现 Skill 或辅助 Skill。
  • Required Skill Call:要求 Node 内必须调用某个 Skill,不替换 Node implementation。例如 executesubagent-execute 必须调用 elementuireview 必须调用 whitebox-code-standard
  • Output Schema:Node 必须产出的文件、状态或 evidence。Output Schema 必须挂到具体 Workflow Node 才算生效;只定义在 workflow.outputSchemas 里不会触发 guard、eval 或 readiness。脚本、eval、readiness 只依赖挂到 Node 的 Output Schema,不依赖 Skill 名称。
  • Guardrail:阻断或放行 Node 推进的检查。
  • Handoff:子代理或跨 Node 交接时必须带回的 evidence。
  • workflow-protocol.json:生成包的唯一运行事实源,kind 为 comet-five-phase-overlayworkflow-kernel

受保护边界

comet-five-phase-overlay 保留 Comet Classic 五阶段主流程和 .comet.yaml 状态语义。普通模式下:

  • comet-five-phase-overlay 的主状态只来自 Classic layout resolver 绑定的 <classic-change-dir>/.comet.yaml;没有 active change 或多个 active changes 时必须阻塞并请用户选择。
  • 不得创建 .comet/runs/<workflow>/state.json 作为 Comet overlay 主状态。Bundle 草稿、eval evidence 和 publish readiness 可以有自己的证据文件,但不能替代 .comet.yaml
  • control Node 不允许 override:openexecuteverifyarchive
  • producer Node 可以 override:designplan,但必须满足对应 Output Schema。
  • handoffguardrail Node 可以 require / augment。
  • 用户坚持替换 control Node 时,改走高级 workflow-kernel,并要求重新声明 state、Output Schema 和 Guardrail。
  • 所有 Node 都必须用 responsibility 说明职责,不使用内部坐标作为用户理解流程的方式。

工作步骤

  1. 恢复现有状态:先运行 comet creator guide --project . --json,展示恢复摘要和下一步。
  2. 读取项目偏好:读取 .comet/skill-preferences.yaml,用 comet creator candidates --json 发现真实本地 Skill,再用 comet skill show <name> --json 读取候选的真实内容与 hash。不得只按名字推测能力。
  3. 生成方案:把用户目标表达为 Workflow Nodes、Skill Bindings、Output Schemas、Guardrails、Handoffs 和 Evidence。
  4. 展示确认页:说明每个 Node 的职责、绑定 Skill、Required Skill Call、Output Schema、可执行披露和 readiness 影响。确认页必须为每个新增 binding 或 schema 显示 enforcement:guardedhandoff-guardedevidence-onlyadvisory
  5. 等待用户确认:未确认前不得写 Bundle draft;存在 missing / ambiguous Skill 时必须暂停。
  6. 初始化后端状态:确认后调用 comet creator init <name> --file <plan.json> --confirmed-proposal --json
  7. 运行创作管线并生成 Bundle:先运行 comet creator authoring-plan <name> --depth quick|full --json 取得 lane DAG。按 DAG 派发 lane——wave1(scriptreferencepause-points)并发派发,wave2(workflow-entryskill-core)在 script 契约之后并发派发,skill-review 作为汇聚 barrier。每个 lane 的产出用 comet creator authoring-record <name> --lane <id> --file <out.json> --json 记录(经 schema 校验;BLOCKED/NEEDS_CONTEXT 会被拒绝)。随后运行 comet creator generate <name> --json:把记录的内容叶子草稿(entry/node SKILL.md、decision-points、recovery)合并进包,而确定性脊梁(protocol/scripts/manifest)保持模板化,并渲染真实审查证据。产出 entry Skill、Node Skills、reference/workflow-protocol.json、六个 scripts、rules、hooks 与 comet/eval.yaml
  8. 验证:展示 quick/full eval 工作量,运行或记录当前 draft hash 的 eval evidence;失败、skip 或证据 hash 过期时不得进入 ready。
  9. Review / readiness:读取 comet publish review <name> --platform <reference-platform> --json,展示 Readiness:Blockers:Warnings:Evidence:
  10. Publish / install preview:人工批准后才能 publish;安装前必须先运行 preview,并展示 No files were written

方案示例

组件库和白盒审查场景应生成类似 plan:

json
{
  "goal": "基于 /comet-classic 的五阶段定制,要求组件库和白盒审查。",
  "skillCreatorIntent": "customize-comet",
  "workflow": {
    "kind": "comet-five-phase-overlay",
    "name": "team-comet",
    "goal": "要求组件库和白盒审查。",
    "nodes": {
      "execute": {
        "requiredSkillCalls": [
          {
            "skill": "elementui",
            "reason": "Use project component library during direct implementation."
          }
        ]
      },
      "subagent-execute": {
        "requiredSkillCalls": [
          {
            "skill": "elementui",
            "scope": "handoff"
          }
        ]
      },
      "review": {
        "requiredSkillCalls": [
          {
            "skill": "whitebox-code-standard",
            "scope": "review"
          }
        ]
      }
    }
  }
}

硬性规则

  • 必须先展示方案确认页,再生成。
  • 确认页必须为每个新增 binding 或 schema 显示 enforcement:guardedhandoff-guardedevidence-onlyadvisory
  • Required Skill Call 不替换 Node implementation。
  • producer override 必须声明 satisfies 的 Output Schema。
  • Output Schema 必须挂到具体 Workflow Node 才算生效;只定义在 workflow.outputSchemas 里不会触发 guard、eval 或 readiness。
  • control Node 普通模式不得 override。
  • eval、review、publish readiness 必须读取同一份 workflow-protocol.json
  • readiness blockers 必须阻止 publish:缺少当前 draft hash 的 eval evidence、人工 approval、required capability 或 executable disclosure 任一项都不能进入 ready。
  • 子代理 Handoff 必须要求子代理加载 Required Skill Call 并回传 evidence。
  • 脚本只读取 protocol 和 state,不把 Skill 名称当成校验依据。
  • 安装前必须询问用户,不得自动安装。

参考资料

  • comet-any/reference/authoring-protocol.json
  • comet-any/reference/authored-zone-example.md
  • comet-any/reference/bundle-authoring.md
  • comet-any/reference/authoring-subagents.md
  • comet-any/reference/eval-provider.md

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 Any AI skill do?

通过 Comet Creator 创建或升级 Comet Classic workflow Skill。不用于一般 Skill 的编写、整理或评审。

Why use Comet Any on TypingMind?

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

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

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 Any?

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

Is the Comet Any 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.

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