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data-pipeline

data-pipeline is an agent for Claude Code from christopherlouet/claude-base. It costs 24 tokens per session (714 once invoked), scanned A, original, MIT.

A workflow for designing data pipelines that collect, transform, validate, and monitor data. ETL transforms data before loading it, while ELT loads it first and transforms it later.

In plain words
What is it for?
Use it to build Airflow or Prefect workflows, write SQL or Python transformations, add data-quality checks, and monitor processing and freshness.
Why use it?
It helps prevent bad, missing, duplicated, or stale data from moving through a system unnoticed. It also covers retries, failure alerts, monitoring, and safe repeatable runs.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter.

not rated 5repo changed 21d ago A scan 24 tokens original MIT

Good fit Use it to build Airflow or Prefect workflows, write SQL or Python transformations, add data-quality checks, and monitor processing and freshness.

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Install with agentmods
npx agentmods add agents/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/agents/christopherlouet/claude-base/data-pipeline/github.svg)](https://agentmods.dev/agents/christopherlouet/claude-base/data-pipeline)
Your own site
<a href="https://agentmods.dev/agents/christopherlouet/claude-base/data-pipeline"><img src="https://agentmods.dev/badge/agents/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/agents/christopherlouet/claude-base/data-pipeline"><img src="https://agentmods.dev/badge/agents/christopherlouet/claude-base/data-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 24 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 714 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 $0.00024 $0.00714
Opus 5.5 $0.00010 $0.00286
Sonnet 5.5 $0.00005 $0.00143
Haiku 4.5 $0.00002 $0.00071

Measured 21d ago against content hash a61264fa0140, 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 21d 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/agents/data-pipeline.md · 53 lines

How it starts

The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DATA-PIPELINE Agent

Design and implementation of ETL/ELT data pipelines.

Workflow

  1. Architecture: choose ETL (complex/sensitive transformation) or ELT (big data/cloud DW)
  2. Orchestration: create Airflow DAG or Prefect Flow with retries and alerts
  3. Transformations: dbt (SQL) or Pandas (Python) depending on context
  4. Data Quality: schema validation, uniqueness/nulls/bounds checks, business rules
  5. Monitoring: Prometheus metrics (records processed, processing time, data freshness)

Tools

  • Orchestration: Airflow, Prefect
  • Transformation: dbt, Pandas
  • Quality: Great Expectations, custom assertions
  • Monitoring: Prometheus counters/histograms/gauges

Expected output

  1. Orchestrated DAG/Flow
  2. SQL/Python transformations
  3. Quality tests
  4. Monitoring and alerts

Guidelines

  • IMPORTANT: Always include quality validations after each load
  • IMPORTANT: Configure retries and email alerts on failure
  • NEVER load data without prior validation
  • YOU MUST monitor data freshness

Think hard about pipeline reliability and idempotency.

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 · 53 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. 21d ago Changed · +10 lines a61264fa0140
  2. 1mo ago First seen · 43 lines · 24 tokens per session scan A 6e72f8e3b3f9

Subscribe to this mod's changes

data-pipeline is an agent published in the GitHub repository christopherlouet/claude-base (5 stars, last pushed 7d ago), licensed MIT. It adds 24 tokens to every session and 714 once invoked, about $0.0001 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.

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