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component-yaml-format
Reference for the Tangle component YAML specification format
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Reference for the Tangle component YAML specification format
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Code review of current PR/commit changes against project coding standards. Use when the user asks for a code review or mentions reviewing changes.
Guidelines for building well-structured, maintainable ML pipelines in Tangle
Analyzes merged PRs from the past week, identifies user-facing changes, and opens a draft PR to the TangleML/website docs repo with updated documentation. Use when running the weekly documentation sync, or when the user invokes /docs-update.
React and React Compiler patterns for this project. Use when writing React components, hooks, providers, or working with React Compiler compatibility.
Run validation and testing commands for the project. Use when the user asks to validate, lint, typecheck, or run tests.
Vitest unit and component testing patterns. Use when writing unit tests, component tests, or hook tests.
| name | Component YAML Format |
| description | Reference for the Tangle component YAML specification format |
name: Component Name
description: What this component does
metadata:
annotations:
cloud_pipelines.net: "true"
inputs:
- name: input_data
type: String
description: Description of input
- name: config
type: String
default: "default_value"
optional: true
outputs:
- name: output_data
type: String
description: Description of output
implementation:
container:
image: python:3.10
command:
- sh
- -c
- |
python3 -c "
# inline Python code
"
args:
- --input
- { inputPath: input_data }
- --output
- { outputPath: output_data }
- --config
- { inputValue: config }
Common input/output types:
String — text data or file pathsInteger — whole numbersFloat — decimal numbersBoolean — true/falseJsonObject — structured JSON dataJsonArray — JSON arraysURI — file URIs or URLsApacheParquet — Parquet files (artifact type)CSV — CSV files (artifact type)Pipelines use implementation.graph instead of implementation.container:
name: My Pipeline
implementation:
graph:
tasks:
task-name:
componentRef:
name: Component Name
spec: { ... }
arguments:
input_name: "{{inputs.pipeline_input}}"
other_input:
taskOutput:
taskId: other-task
outputName: output_name
outputValues:
pipeline_output:
taskOutput:
taskId: final-task
outputName: result
{{inputs.name}} — reference a pipeline-level input{{tasks.taskName.outputs.outputName}} — reference a task output{graphInput: {inputName: name}} — object form of input reference{taskOutput: {taskId: name, outputName: name}} — object form of task output reference