factory-data-pipelines

factory-data-pipelines is a skill for Claude Code from nonlinear-xyz/factory-kit. It costs 89 tokens per session (2,355 once invoked), scanned A, original, MIT.

A set of rules for importing data and running data-processing services. It covers CSV files, time-series data stored in JSONB, and Python services that can be started from a command line, a Cloud Run API, or Pub/Sub.

In plain words
What is it for?
Use it to build CSV import scripts, store flexible time-series data, and organize Python services used with Next.js projects. It also covers YAML configuration and database transactions for imports.
Why use it?
It helps avoid adding a large job framework or inconsistent service structure for simple data work. It gives related import scripts and services a predictable shape.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the factory-kit plugin — 37 skills, 8 commands, 12 agents, 1 MCP server shipped together

Good fit Use it to build CSV import scripts, store flexible time-series data, and…

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Install with agentmods
npx agentmods add skills/nonlinear-xyz/factory-kit/factory-data-pipelines
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.

Any agent
npx skills add nonlinear-xyz/factory-kit --skill factory-data-pipelines
Clone the repo
git clone --depth 1 https://github.com/nonlinear-xyz/factory-kit

Made for: Claude Code.

Or install factory-kit, the plugin that ships this one along with the rest of its 37 skills, 8 commands, 12 agents, 1 MCP server.

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 factory-data-pipelines

README.md
[![agentmods](https://agentmods.dev/badge/skills/nonlinear-xyz/factory-kit/factory-data-pipelines.svg)](https://agentmods.dev/skills/nonlinear-xyz/factory-kit/factory-data-pipelines)
Your own site
<a href="https://agentmods.dev/skills/nonlinear-xyz/factory-kit/factory-data-pipelines"><img src="https://agentmods.dev/badge/skills/nonlinear-xyz/factory-kit/factory-data-pipelines.svg" alt="Measured on agentmods" height="20"></a>
Per session 89 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,355 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 $0.00089 $0.02355
Opus 5 $0.00044 $0.01177
Sonnet 5 $0.00018 $0.00471
Haiku 4.5 $0.00009 $0.00235

Measured 7d ago against content hash fad0d219ae8d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

factory-data-pipelines 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 7d 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.

skills/factory-data-pipelines/SKILL.md · 194 lines

How it starts

The opening of the file, as written. The whole thing — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Factory data pipelines

Each section leads with Principle (one sentence, stack-agnostic), then Why (constraint → option → tradeoff), then Recipe (the Papa Parse / FastAPI / Cloud Run shape we use), and Failure mode when there's one to name. Sections that are pure style with no deeper truth are marked Recipe only.

CSV ingestion — a script, not a framework

Principle. A one-shot CSV importer is a standalone script in scripts/; promote to a framework only when a second consumer appears.

Why. Premature job-framework adoption for a single CSV importer is paying the abstraction cost without the abstraction benefit. A standalone script with Papa Parse and a Drizzle transaction is grep-able, debuggable, runnable locally. Wrapping it in BullMQ / Inngest / a Cloud Run job buys nothing until there's a second importer that shares the wrapper.

Recipe.

scripts/
└── data_processing/
    ├── import-state-data.ts
    ├── simulations/
    │   └── import-simulation.ts
    └── vins/
        └── import-vins.ts
import Papa from 'papaparse';
import { db } from '@/db';
import { foo } from '@/db/schema';

const { data } = Papa.parse<FooRow>(csvText, { header: true, skipEmptyLines: true });

await db.transaction(async (tx) => {
  for (const row of data) {
    await tx.insert(foo).values({ /* ... */ }).onConflictDoUpdate({ /* ... */ });
  }
});

Time-series / event storage — JSONB envelope

Principle. What drives queries gets a real column. What doesn't goes in a JSONB envelope. The schema inside JSONB can evolve without a migration.

Why. Time-series data and event streams have an outer schema (the row) and an inner schema (the payload). The outer schema needs to be queryable — filter by fleetId, sort by time, join across rows. The inner schema is consumed by application code that already speaks its types, doesn't need a SQL index, and may evolve faster than migrations can keep up. JSONB envelope splits these clean: columns for outer, JSONB for inner. The trap is querying inside JSONB at app speed — once you're doing that, the field has earned a column.

Read the full file on GitHub · 194 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. 7d ago First seen · 194 lines · 89 tokens per session scan A fad0d219ae8d

Subscribe to this mod's changes

factory-data-pipelines is a skill published in the GitHub repository nonlinear-xyz/factory-kit (9 stars, last pushed 1mo ago), licensed MIT. It adds 89 tokens to every session and 2,355 once invoked, about $0.0004 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 2026-08-31.

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