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data-pipeline

data-pipeline is a command for Claude Code from christopherlouet/claude-base. It costs 0 tokens per session (740 once invoked), scanned A, original, MIT.

A command for building data pipelines, which move data from sources through checks and changes into a destination. ETL means extract, transform, load; ELT loads data before transforming it.

In plain words
What is it for?
Use it to connect data sources, clean and validate records, load databases or files, schedule processing, and track errors and results.
Why use it?
It provides a structured way to handle validation, failures, scheduling, and monitoring instead of managing each data movement step separately.

Command for Claude Code

Written for Claude Code: $ARGUMENTS substitution.

not rated 5repo changed 16d ago A scan 0 tokens original MIT

Good fit Use it to connect data sources, clean and validate records, load databases or files, schedule processing, and track errors and results.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/christopherlouet/claude-base/data-pipeline
View source ↗ christopherlouet/claude-base christopherlouet.github.io
Install

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.

Clone the repo
git clone --depth 1 https://github.com/christopherlouet/claude-base

Made for: Claude Code.

Wrote 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.

agentmods badge for data-pipeline

README.md
[![agentmods](https://agentmods.dev/badge/commands/christopherlouet/claude-base/data-pipeline/github.svg)](https://agentmods.dev/commands/christopherlouet/claude-base/data-pipeline)
Your own site
<a href="https://agentmods.dev/commands/christopherlouet/claude-base/data-pipeline"><img src="https://agentmods.dev/badge/commands/christopherlouet/claude-base/data-pipeline/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.

agentmods 80×15 button for data-pipeline

Your own site · 80×15
<a href="https://agentmods.dev/commands/christopherlouet/claude-base/data-pipeline"><img src="https://agentmods.dev/badge/commands/christopherlouet/claude-base/data-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 740 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.00740
Opus 5.5 $0.00000 $0.00296
Sonnet 5.5 $0.00000 $0.00148
Haiku 4.5 $0.00000 $0.00074

Measured 16d ago against content hash a35c5d1712ce, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

data-pipeline 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 16d 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.

.claude/commands/data/data-pipeline.md · 59 lines

How it starts

The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent DATA-PIPELINE

Design and implement ETL/ELT data pipelines.

Request context

$ARGUMENTS

Objective

Create a robust data pipeline with extraction, transformation, loading, validation, error handling and monitoring.

Workflow

  • Analyze needs: sources, frequency, volume, transformations, destination
  • Choose the pattern (Batch/Airflow, Streaming/Kafka, Micro-batch/Spark, ELT/dbt)
  • Structure the project (extractors, transformers, loaders, orchestration, schemas, tests)
  • Implement extraction from sources
  • Define validation schemas (Pydantic or equivalent)
  • Implement transformations with validation at each step
  • Load to destination
  • Add error handling (retry with exponential backoff, dead letter queue)
  • Configure orchestration (Airflow DAG or equivalent)
  • Set up monitoring (records processed, duration, errors, alerts)

Expected output

Pipeline with sources, documented transformations, destination (format, partitioning), orchestration (cron, SLA) and monitoring (metrics, alerts).

Agent When to use it
/data:data-modeling Model the data
/growth:growth-analytics Analyze the results (cohort, RFM, KPIs)
/ops:ops-monitoring Configure monitoring
/dev:dev-tdd Test the pipeline

IMPORTANT: Always validate data at each step.

YOU MUST implement robust error handling (retry, DLQ).

NEVER lose data - use checkpoints and idempotence.

Think hard about pipeline scalability and maintainability.

See also

The orchestrator and transformation vendors publish their own skills — install the one matching the stack, as skill folders (recipe: docs/recipes/recommended-vendor-skills.md §"Stack-specific"):

  • Airflow — astronomer/agents (Apache-2.0, pin 1ec1a1fa): airflow (the entry point the others hand off to), authoring-dags, testing-dags, debugging-dags, migrating-airflow-2-to-3. They drive Airflow through Astronomer's af CLI (astro-airflow-mcp, installed unpinned by uv tool install) and the Astro CLI for tests — Astronomer tooling, with a paid platform (Astro) behind it.
  • Dagster — dagster-io/skills plugins/dagster/skills/dagster-expert (Apache-2.0, v1.13.25 = commit b08dd8e6). Its description claims every "data pipelines" task: install it only in Dagster projects. The plugin also registers the remote Dagster+ MCP server (paid); the skill folder alone does not.
  • dbt — dbt-labs/dbt-agent-skills skills/dbt/skills/* (Apache-2.0, pin 168a2b0b): models, tests and unit tests, documentation, semantic layer, mesh. Not skills/dbt-migration/: its upgrade script runs uvx --from git+… against an unpinned branch.

Read the full file on GitHub · 59 lines

Changes

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.

  1. 16d ago Changed · +10 lines a35c5d1712ce
  2. 1mo ago First seen · 49 lines · 0 tokens per session scan A 7c570725b366

Subscribe to this mod's changes

data-pipeline is a command published in the GitHub repository christopherlouet/claude-base (5 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 740 tokens. 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.

Claude CodeData and AIagentic-aiai-codinganthropicclaude-aicli-tool
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