pipeline

Coordinates end-to-end source processing pipelines from seed to archive via resumable, queue-driven phases.

1|Updated Mar 6, 2026
One-click install
npx skills add https://github.com/adiman9/mnemos --skill pipeline-adiman9
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pipeline
Source: https://github.com/adiman9/mnemos/tree/main/core/skills/pipeline
Command: npx skills add https://github.com/adiman9/mnemos --skill pipeline-adiman9

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates the end-to-end orchestration of source processing pipelines, from seed to archive, reducing manual coordination and errors.

Core Features & Use Cases

  • End-to-end phase orchestration (seed, extract, process, verify, archive)
  • Resumable, queue-driven state management across batches
  • Vault/workspace context awareness and domain vocabulary adherence
  • Use cases include processing large document batches with traceable outputs and auditable histories

Quick Start

Run the pipeline on a target batch to execute seed, extract, process, verify, and archive end-to-end.

Frequently Asked Questions about pipeline

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I orchestrate an end-to-end document processing pipeline from seed to archive?

You orchestrate an end-to-end document processing pipeline by executing coordinated phases for seed, extract, process, verify, and archive. This automates source ingestion and archiving workflows, reducing manual coordination and errors across batches.

What is queue-driven state management for batch processing pipelines?

Queue-driven state management is a resumable mechanism that tracks pipeline progress across batches. It maintains state for seed, extract, process, verify, and archive phases, ensuring workflows can recover from interruptions without losing data.

Can I resume a document extraction and verification pipeline if it fails mid-batch?

Yes, you can resume a document extraction and verification pipeline if it fails mid-batch. The orchestration uses resumable, queue-based state management with robust error handling, allowing interrupted workflows to recover and continue processing.

What's the best way to automate vault ingestion and archiving workflows for large document batches?

The best way to automate vault ingestion and archiving workflows is using an orchestration pipeline with workspace context awareness. It processes large document batches end-to-end, producing traceable outputs and auditable histories across vaults.

Does pipeline orchestration support domain vocabulary adherence during document ingestion?

Yes, pipeline orchestration supports domain vocabulary adherence during document ingestion. It features vault and workspace context awareness, ensuring that extraction, processing, and verification phases align with your specific domain vocabulary.