9 bundled workflow templates: - data-pipeline: ETL extract/transform/validate - content-review: multi-agent draft/quality/accuracy/edit - customer-support: tiered triage/response/escalation - code-review: parallel correctness+security+style analysis - research: research/fact-check/summarize - content-pipeline: research → write → edit article creation - translate-polish: auto-detect language, translate, review - brainstorm: ideation → evaluation → action plan - weekly-report: raw notes → organized → polished report
33 lines
1.4 KiB
TOML
33 lines
1.4 KiB
TOML
id = "data-pipeline"
|
|
name = "Data Pipeline"
|
|
description = "ETL pipeline that extracts data from a source, transforms it into a target format, and validates the output for completeness and correctness."
|
|
category = "data"
|
|
tags = ["etl", "data", "pipeline", "transform"]
|
|
|
|
[[parameters]]
|
|
name = "data_source"
|
|
description = "URL or file path to the data source"
|
|
param_type = "string"
|
|
required = true
|
|
|
|
[[parameters]]
|
|
name = "output_format"
|
|
description = "Desired output format (json, csv, markdown)"
|
|
param_type = "string"
|
|
required = false
|
|
default = "json"
|
|
|
|
[[steps]]
|
|
name = "extract"
|
|
prompt_template = "Extract raw data from the following source: {{data_source}}. Return the complete dataset without any transformation, preserving the original structure."
|
|
|
|
[[steps]]
|
|
name = "transform"
|
|
prompt_template = "Transform the following raw data into well-structured {{output_format}} format. Apply standard cleaning: trim whitespace, normalise dates to ISO-8601, remove duplicate rows, and convert empty strings to null.\n\nRaw data:\n{{extract}}"
|
|
depends_on = ["extract"]
|
|
|
|
[[steps]]
|
|
name = "validate"
|
|
prompt_template = "Validate the transformed data below for completeness and correctness. Check for: missing required fields, type mismatches, invalid date formats, out-of-range values, and referential integrity. Return a validation report with pass/fail status and any issues found.\n\nTransformed data:\n{{transform}}"
|
|
depends_on = ["transform"]
|