Pipeline Model Interpreter logo

Pipeline Model Interpreter

OrganizationPopular
TencentBlueKing
pipeline-model-interpreter

解释 BK-CI 流水线或创作流的 Model JSON，帮助 AI 理解 Model -> Stage -> Container(Job) -> Element 的含义、启动参数、矩阵、Finally、审核与常见插件语义。用户贴出流水线 JSON、创作流 JSON、编排数据，或询问某个 Stage/Job/插件/atomCode/stepId 含义时使用。

Overview

PublisherTencentBlueKing
Repositorybk-ci
Skill namepipeline-model-interpreter
Stars
2.5K
Forks
524
Bundled files
3
Links
Skill sourceRepositoryHomepage
  • 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.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by TencentBlueKing on GitHub. Read the source before you install it.

Installation

Install the Pipeline Model Interpreter 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/TencentBlueKing/bk-ci.git /tmp/bk-ci
mkdir -p .claude/skills
cp -r /tmp/bk-ci/ai/skills/pipeline-model-interpreter .claude/skills/pipeline-model-interpreter
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pipeline Model Interpreter 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 Pipeline Model Interpreter 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 Pipeline Model Interpreter 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.

流水线模型解释

适用场景

  • 用户直接贴出 BK-CI 流水线或创作流的 Model JSON
  • 用户问“这个流水线做了什么”“这个编排什么意思”“帮我理解这个 Stage/Job/插件”
  • 用户要解释启动参数、矩阵、Finally、审核、脚本插件、商店插件输入输出
  • 用户给出 atomCode、elementId、stepId、jobId 等信息，要求说明其在编排中的含义

不适用场景

  • 修改模型代码、加字段、做兼容性改造
  • 排查构建运行时失败日志或执行状态
  • 设计固定摘要模板输出
  • 需要理解 YAML 转换、持久化、版本兼容实现细节

快速指导

  1. 先把 JSON 还原成 Model -> Stage -> Container -> Element 四层结构。
  2. 第一个 Stage 里的 TriggerContainer.params 优先解释为启动参数入口；触发器插件本身通常不用当业务步骤展开。
  3. 先判断容器类型：trigger、vmBuild、normal，再判断插件类型：linuxScript、windowsScript、marketBuild、marketBuildLess、subPipelineCall、manualReviewUserTask 等。
  4. 解释插件时同时看 @type、atomCode、name、data.input、data.output 和 additionalOptions。
  5. 如果用户问整体含义，先说明主流程、关键 Stage/Job、启动参数入口和可能产出；如果只问某个节点，只解释相关切片。
  6. 遇到未知 atomCode 时，不臆测功能；明确标注“需结合插件文档确认”，并列出关键输入输出字段。
  7. 解释某节点的执行时机时，结合 runCondition 判断；Element / Job / Stage 三层各有独立枚举，不要混用。
  8. 详细分析步骤、常见插件速查和参数类型速查看 reference/。

高信号规则

  • 创作流与流水线使用同一套模型结构，这个 skill 同时适用于两者
  • containerHashId、jobId、element.id、stepId 语义不同，不能混用
  • status、startEpoch、elapsed、executeCount、timeCost 等运行态字段默认忽略，除非用户明确问运行状态
  • additionalOptions.enable=false、jobControlOption.enable=false、stageControlOption.enable=false 要明确标注为已禁用
  • 敏感参数或 PASSWORD 类型只标注为敏感，不回显默认值

关键陷阱

  • 把 TriggerContainer 里的触发器插件当成业务主流程
  • 把运行态字段当成编排语义来解释
  • 忽略矩阵展开后的子 Job、Finally Stage、审核控制和互斥组
  • 只看 atomCode 不看 data.input / data.output，导致插件理解失真
  • 对未知商店插件直接猜功能，而不是保守说明边界

延伸阅读

  • 详细分析步骤：reference/1-json-analysis-playbook.md
  • 容器、插件与参数类型速查：reference/2-common-plugin-and-container-hints.md
  • classType / dispatchType / 枚举字面量清单：reference/3-classtype-and-enum-catalog.md
  • 如果用户手里没有 Model JSON、想先取回来，可用 managing-devops-pipeline 或构建 Agent 的编排查询工具（获取流水线编排摘要/获取流水线编排）
  • 如果需要理解模型代码结构、版本兼容或 YAML 转换：pipeline-model-architecture

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 Pipeline Model Interpreter AI skill do?

解释 BK-CI 流水线或创作流的 Model JSON，帮助 AI 理解 Model -> Stage -> Container(Job) -> Element 的含义、启动参数、矩阵、Finally、审核与常见插件语义。用户贴出流水线 JSON、创作流 JSON、编排数据，或询问某个 Stage/Job/插件/atomCode/stepId 含义时使用。

Why use Pipeline Model Interpreter on TypingMind?

Because you install it once and use it with any model. Pipeline Model Interpreter 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 Pipeline Model Interpreter in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/TencentBlueKing/bk-ci/tree/master/ai/skills/pipeline-model-interpreter. 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 Pipeline Model Interpreter?

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 Pipeline Model Interpreter?

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

Is the Pipeline Model Interpreter AI skill free?

It is published on GitHub by TencentBlueKing. Check the repository for licensing terms. 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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