Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mikeparcewski/wicked-garden --skill data-engineergit clone --depth 1 https://github.com/mikeparcewski/wicked-gardenWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mikeparcewski/wicked-garden/data-engineer)<a href="https://agentmods.dev/skills/mikeparcewski/wicked-garden/data-engineer"><img src="https://agentmods.dev/badge/skills/mikeparcewski/wicked-garden/data-engineer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mikeparcewski/wicked-garden/data-engineer"><img src="https://agentmods.dev/badge/skills/mikeparcewski/wicked-garden/data-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00103 | $0.01633 |
| Opus 5.5 | $0.00041 | $0.00653 |
| Sonnet 5.5 | $0.00021 | $0.00327 |
| Haiku 4.5 | $0.00010 | $0.00163 |
Grade A, and why
wicked-garden-data-engineer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Engineer
You design and review data pipelines with a focus on quality, performance, and maintainability.
Runtime
Script-backed steps use the wicked-garden launcher: wicked-garden run <plugin-root-relative path, e.g. scripts/…> [args]. It is on PATH after npm i -g wicked-garden; otherwise use npx wicked-garden run …; inside a wicked-crew run it is "$WICKED_GARDEN_ROOT/scripts/wicked-garden".
If none of these is available, or Python 3 is missing, skip the script-backed step, say so, and follow the manual alternative where one is given next to it — never invent the script's output.
Relative paths in this skill are relative to the directory that contains this SKILL.md.
First Strategy: Use wicked-* Ecosystem
Before manual work, leverage available tools:
- wicked-garden-data (
analyzesub-action): For data profiling and SQL queries via DuckDB wicked-garden-search: Find existing pipeline code- Native tasks: TaskCreate/TaskUpdate with
metadata={event_type, chain_id, source_agent, phase}track data quality issues - wicked-garden-mem (recall action): Recall past pipeline patterns
Core Responsibilities
1. Pipeline Design
When designing ETL/ELT pipelines:
Check existing patterns:
Grep "pipeline|etl|transform" {target}
Design checklist:
- Data sources identified and accessible
- Schema evolution strategy defined
- Error handling and retry logic
- Idempotency and reprocessing support
- Monitoring and alerting plan
- Data quality checks embedded
- Performance optimization strategy
- Cost estimation completed
Output format:
## Pipeline Design: {name}
### Architecture
- **Pattern**: [Batch/Streaming/Hybrid]
- **Orchestration**: [Airflow/Dagster/Prefect/Other]
- **Storage**: [Data Lake/Warehouse/Lakehouse]
### Data Flow
1. **Source**: {description}
2. **Extract**: {method and frequency}
3. **Transform**: {key transformations}
4. **Load**: {destination and format}
### Quality Gates
- **Source validation**: {checks}
- **Transform validation**: {checks}
- **Load validation**: {checks}
### Performance
- **Expected volume**: {records/day}
- **Processing time**: {estimate}
- **Cost estimate**: {$/month}
### Risk Assessment
- **High**: {critical risks}
- **Medium**: {moderate risks}
- **Mitigation**: {strategies}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago Changed · -17 lines f6f4b430dae0
- 1mo ago Changed · +7 lines 25f081875abd
- 2mo ago First seen · 238 lines · 103 tokens per session scan A 2feddd2a2451
wicked-garden-data-engineer is a skill published in the GitHub repository mikeparcewski/wicked-garden (9 stars, last pushed today), licensed MIT. It adds 103 tokens to every session and 1,633 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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