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 agentmods add skills/daffy0208/ai-dev-standards/data-engineernpx skills add daffy0208/ai-dev-standards --skill data-engineergit clone --depth 1 https://github.com/daffy0208/ai-dev-standardsWrote 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/daffy0208/ai-dev-standards/data-engineer)<a href="https://agentmods.dev/skills/daffy0208/ai-dev-standards/data-engineer"><img src="https://agentmods.dev/badge/skills/daffy0208/ai-dev-standards/data-engineer.svg" alt="Measured on agentmods" 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 | $0.00016 | $0.04563 |
| Opus 5 | $0.00008 | $0.02282 |
| Sonnet 5 | $0.00003 | $0.00913 |
| Haiku 4.5 | $0.00002 | $0.00456 |
Grade A, and why
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 4d 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 — 870 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Engineer Skill
I help you build robust data pipelines, ETL processes, and data infrastructure.
What I Do
Data Pipelines:
- Extract, Transform, Load (ETL) processes
- Data ingestion from multiple sources
- Batch and real-time processing
- Data quality validation
Data Infrastructure:
- Database schema design
- Data warehousing
- Caching strategies
- Data replication
Analytics:
- Data aggregation
- Metrics calculation
- Report generation
- Data export
ETL Patterns
Pattern 1: Simple ETL Pipeline
Use case: Daily sync from external API to database
// lib/etl/daily-sync.ts
interface RawCustomer {
id: string
full_name: string
email_address: string
signup_date: string
}
interface Customer {
id: string
name: string
email: string
signupDate: Date
}
export async function syncCustomers() {
console.log('Starting customer sync...')
// EXTRACT: Fetch data from external API
const response = await fetch('https://api.example.com/customers', {
headers: {
Authorization: `Bearer ${process.env.API_KEY}`
}
})
const rawCustomers: RawCustomer[] = await response.json()
console.log(`Extracted ${rawCustomers.length} customers`)
// TRANSFORM: Clean and normalize data
const transformedCustomers: Customer[] = rawCustomers.map(raw => ({
id: raw.id,
name: raw.full_name.trim(),
email: raw.email_address.toLowerCase(),
signupDate: new Date(raw.signup_date)
}))
// LOAD: Insert into database
let inserted = 0
let updated = 0
for (const customer of transformedCustomers) {
const existing = await db.customers.findUnique({
where: { id: customer.id }
})
if (existing) {
await db.customers.update({
where: { id: customer.id },
data: customer
})
updated++
} else {
await db.customers.create({
data: customer
})
inserted++
}
}
console.log(`Sync complete: ${inserted} inserted, ${updated} updated`)
return { inserted, updated, total: transformedCustomers.length }
}
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 870 lines · 16 tokens per session scan A 873316a2549d
data-engineer is a skill published in the GitHub repository daffy0208/ai-dev-standards (36 stars, last pushed 8mo ago), licensed MIT. It adds 16 tokens to every session and 4,563 once invoked, about $0.0001 per session on Opus 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 2026-08-30.
Other skills, from other repositories
Data Pipeline Engineering
Guide for designing, building, and maintaining reliable data pipelines.
data-migration
Activate when the genjob agent detects that the source and target databases differ. Covers cross-database transfer lifecycle - type mapping via adapter Mixin hints, DDL generation, data transfer via transferqueryresult, and lightweight reconciliation.
data-pipeline
Production data pipeline patterns — ETL/ELT design, orchestration with Airflow/Prefect, idempotency, incremental loads, and data quality.
operator-verify
Bootstrap and verify Operator ETL in one command — Python check, uv install, sync deps, full proof gate. Use on first clone, "does it work", setup, or before any other operator skill.
operator-run
Run Operator ETL locally — MVP demo, pytest, FOIA graph pipeline, Streamlit dashboard. Use when proving the system works or demoing to reviewers.
operator-ship-gcp
Deploy Operator ETL to GCP — Terraform, Docker, Cloud Build, Cloud Run, BigQuery. Use when lifting from local DuckDB MVP to staging/production infrastructure.