원클릭으로
component-yaml-format
Reference for the Tangle component YAML specification format
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
메뉴
Reference for the Tangle component YAML specification format
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
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