aps-doc-staging
Expert documentation generation for staging transformation layers. Auto-detects SQL engine (Presto/Trino vs Hive), documents transformation rules, PII handling, deduplication strategies, and data quality rules. Use when documenting staging transformations.
Best use case
aps-doc-staging is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Expert documentation generation for staging transformation layers. Auto-detects SQL engine (Presto/Trino vs Hive), documents transformation rules, PII handling, deduplication strategies, and data quality rules. Use when documenting staging transformations.
Teams using aps-doc-staging should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/aps-doc-staging/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How aps-doc-staging Compares
| Feature / Agent | aps-doc-staging | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Expert documentation generation for staging transformation layers. Auto-detects SQL engine (Presto/Trino vs Hive), documents transformation rules, PII handling, deduplication strategies, and data quality rules. Use when documenting staging transformations.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# APS Staging Transformation Documentation Expert
Specialized skill for generating comprehensive documentation for staging transformation layers. Automatically detects SQL engines, extracts transformation rules, documents PII handling, and analyzes deduplication strategies.
## When to Use This Skill
Use this skill when:
- Documenting staging transformation workflows
- Creating documentation for data cleaning and standardization logic
- Documenting PII handling and security transformations
- Creating documentation for deduplication strategies
- Documenting data quality rules and validations
- Generating documentation for Presto/Trino or Hive transformations
**Example requests:**
```
"Document the staging transformation for customer events"
"Create staging layer documentation with transformation rules"
"Document PII handling in staging transformations"
"Generate staging documentation following this template: [Confluence URL]"
```
---
## 🚨 MANDATORY: Codebase Access Required
**WITHOUT codebase access = NO documentation. Period.**
**If no codebase access provided:**
```
I cannot create technical documentation without codebase access.
Required:
- Directory path to staging workflows
- Access to .dig, .sql, .yml files
Without access, I cannot extract real transformation SQL, PII logic, or table names.
Provide path: "Code is in /path/to/staging/"
```
**Before proceeding:**
1. Ask for codebase path if not provided
2. Use Glob to verify SQL files exist
3. STOP if cannot read files
**Documentation MUST contain:**
- Real transformation SQL from .sql files
- Actual PII hashing/masking logic
- Real table/column names
- Working SQL examples from code
**NO generic placeholders. Only real, extracted data.**
## REQUIRED Documentation Template
**Follow this EXACT structure (analyzed from production examples):**
```markdown
# Staging Transformation - {Engine} Engine
## Overview
**Engine**: {Presto/Trino or Hive}
**Architecture**: {Loop-based / Other}
**Processing Mode**: {Incremental / Full}
**Location**: {directory path}
### Key Characteristics
{List key features from actual workflow}
---
## Architecture Overview
### Directory Structure
{Actual directory tree from codebase}
### Core Components
#### 1. Main Workflow File
{Name and purpose}
**Key Features:**
- {Feature from actual .dig file}
- {Feature from actual .dig file}
**Workflow Phases:**
{Extract from actual workflow}
#### 2. Configuration File
{Name and structure from actual codebase}
**Configuration Structure:**
{Real YAML structure}
**Table Configuration Fields:**
{Document actual fields used}
#### 3. SQL Transformation Files
{Types: init, incremental, upsert - from actual codebase}
---
## Processing Flow
### Initial Load (First Run)
{Step-by-step from actual workflow}
### Incremental Load (Subsequent Runs)
{Step-by-step from actual workflow}
---
## Data Transformation Rules
{Document ACTUAL transformation rules from codebase}
### 1. Date/Timestamp Processing
{Real SQL examples from transformation files}
### 2. String Standardization
{Real SQL examples}
### 3. JSON Extraction
{Real examples if exists}
### 4. Email Processing
{Real examples if exists}
### 5. Phone Number Processing
{Real examples if exists}
### 6. Deduplication Logic
{Real ROW_NUMBER() or DISTINCT logic}
### 7. Metadata Columns
{Real source_system, load_timestamp columns}
---
## Table-Specific Transformation Rules
{If using reference table like staging_trnsfrm_rules:}
**Reference Table**: {database}.{table}
**Purpose**: {explain}
**Schema**: {real schema}
**How Used**: {explain how workflow reads these rules}
---
## Current Implementation
**Configured Tables**:
{List actual tables from config}
---
## How to Add New Source Tables
{Step-by-step with real examples}
---
## Monitoring & Troubleshooting
**Key Queries**:
{Real SQL for checking status, data quality}
**Common Issues**:
{Real issues and solutions}
---
## Best Practices
{List from actual production experience}
---
## Summary
{Brief recap of capabilities}
```
---
**Template Usage Notes:**
- Read actual workflows (.dig), configs (.yml), SQL files
- Extract REAL transformation logic from SQL
- Document REAL deduplication strategies
- Use actual table/column names from codebase
- Include working SQL examples
- NO placeholders - only real extracted data
## Summary
This skill generates production-ready staging documentation by:
- Reading actual .dig workflows, .yml configs, and .sql files
- Following the exact template structure shown above
- Extracting real transformation rules from SQL
- Documenting actual deduplication logic
- Creating comprehensive documentation with working SQL examples
**Key capability:** Transforms staging codebase into professional Confluence documentation with all transformation rules documented.Related Skills
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