ai-pipeline-orchestration

ai-pipeline-orchestration is a skill for Claude Code, Codex from ranbot-ai/awesome-skills. It costs 39 tokens per session (1,235 once invoked), scanned A, original, no licence file.

An AI and machine-learning workflow guide for moving data, training models, running batch predictions, and building RAG indexes. RAG, or retrieval-augmented generation, lets a model answer using information retrieved from a document store.

In plain words
What is it for?
Use it to plan data ingestion, model training, batch inference, and RAG indexing pipelines.
Why use it?
It helps coordinate multi-step jobs that would otherwise need to be run and monitored by hand. It covers Prefect, Airflow, and Dagster, which are tools for scheduling workflows.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Use it to plan data ingestion, model training, batch inference, and RAG indexing pipelines.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ranbot-ai/awesome-skills/ai-pipeline-orchestration
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 ranbot-ai/awesome-skills --skill ai-pipeline-orchestration
Clone the repo
git clone --depth 1 https://github.com/ranbot-ai/awesome-skills

Made for: Claude Code, Codex.

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 ai-pipeline-orchestration

README.md
[![agentmods](https://agentmods.dev/badge/skills/ranbot-ai/awesome-skills/ai-pipeline-orchestration/github.svg)](https://agentmods.dev/skills/ranbot-ai/awesome-skills/ai-pipeline-orchestration)
Your own site
<a href="https://agentmods.dev/skills/ranbot-ai/awesome-skills/ai-pipeline-orchestration"><img src="https://agentmods.dev/badge/skills/ranbot-ai/awesome-skills/ai-pipeline-orchestration/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 ai-pipeline-orchestration

Your own site · 80×15
<a href="https://agentmods.dev/skills/ranbot-ai/awesome-skills/ai-pipeline-orchestration"><img src="https://agentmods.dev/badge/skills/ranbot-ai/awesome-skills/ai-pipeline-orchestration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,235 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 unknown 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 $0.00039 $0.01235
Opus 5.5 $0.00016 $0.00494
Sonnet 5.5 $0.00008 $0.00247
Haiku 4.5 $0.00004 $0.00123

Measured yesterday against content hash 4e46263a774a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ai-pipeline-orchestration 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 yesterday.

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/ai-pipeline-orchestration/SKILL.md · 138 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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. yesterday Changed · -15 lines 4e46263a774a
  2. 26d ago First seen · 153 lines · 39 tokens per session scan A 2b67605237c9

Subscribe to this mod's changes

ai-pipeline-orchestration is a skill published in the GitHub repository ranbot-ai/awesome-skills (7 stars, last pushed yesterday), with no licence file. It adds 39 tokens to every session and 1,235 once invoked, about $0.0002 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 2026-09-21.

Related

Other skills, from other repositories

leiloeiro-edital-ranbot-ai

Analise e auditoria de editais de leilao judicial e extrajudicial. Riscos ocultos, clausulas perigosas, debitos, ocupante e classificacao da oportunidade.

ThomasMoreAI/legal-skills-open · 51 tokens

dify

Use when building LLM applications with visual workflow — RAG knowledge bases, AI agents, chatbots with drag-and-drop orchestration. Dify: open-source LLM app platform supporting 30+ models (OpenAI, Claude, DeepSeek, Ollama, Qwen, GLM) with Docker deployment.

znlgis/opengis-skills · 66 tokens

ai-skills

Use when building LLM applications, RAG knowledge bases, AI agents, terminal coding agents, multi-model orchestration, plugin-based agent harnesses, or file translation. Index of 14 skills: Dify, LangChain, LlamaIndex, Ollama, Transformers, Hermes Agent, OpenClaw, OpenCode, Pi, DocuTranslate, DeepSeek Harness and more.

znlgis/opengis-skills · 81 tokens

dify-workflow

Use when dify AI workflow platform — LLM apps, knowledge bases, agents, workflow orchestration, API deployment. Use when working with dify workflow.

oyi77/1ai-skills · 37 tokens

memory-rag-poisoning-detection

Detect persistent-memory poisoning and RAG/knowledge-base contamination via dialogue testing. Use when the agent has long-term memory, a user/preference store, or writes to a retrievable knowledge base.

Tencent/AI-Infra-Guard · 48 tokens

browserwing-executor

Control browser automation through HTTP API. Supports page navigation, element interaction (click, type, select), data extraction, accessibility snapshot analysis, screenshot, JavaScript execution, and batch operations.

MemTensor/MemOS · 42 tokens