dag-result-aggregator

Name: dag-result-aggregator
Availability: InStock
Author: Curiositech

Merge parallel DAG branch outputs into a single structured result.

10|1|Updated Mar 17, 2026

Search Tags:#orchestration #merge #parallel #conflict-resolution #aggregate #dag #data-processing

Ready to run

npx skills add https://github.com/curiositech/windags-skills --skill dag-result-aggregator

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dag-result-aggregator
Source: https://github.com/curiositech/windags-skills/tree/main/skills/dag-result-aggregator
Command: npx skills add https://github.com/curiositech/windags-skills --skill dag-result-aggregator

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Parallel DAGs generate multiple outputs that must be combined into a single coherent result. The DAG Result Aggregator coordinates collection, conflict resolution, and formatting for downstream consumption.

Core Features & Use Cases

Result collection from all parallel branches
Multiple merge strategies (union, intersection, priority, weighted, deep merge)
Conflict resolution with provenance tracking
Output formatting and validation for downstream nodes

Quick Start

Provide the completed outputs from all parallel DAG branches; this skill will merge them into a single, structured result.

Frequently Asked Questions about dag-result-aggregator

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

FAQPage Schema

How do I merge parallel DAG branch outputs into a single result?▼

To merge parallel DAG outputs, the aggregator collects completed results from all branches, applies a selected merge strategy like union or deep merge, resolves conflicts with provenance tracking, and formats a single structured result.

What merge strategies can I use to aggregate parallel data processing outputs?▼

Merge strategies for aggregating parallel outputs include union, intersection, priority, weighted, and deep merge. Each strategy defines how conflicting data points from multiple DAG branches are combined into the final coherent result.

How does conflict resolution work when consolidating findings from multiple parallel analyses?▼

Conflict resolution during result consolidation tracks the provenance of each output from parallel branches. This ensures you know exactly which branch contributed conflicting data points when the aggregator merges them into a single structured result.

When do I need to aggregate outputs from parallel DAG branches?▼

You need to aggregate parallel DAG outputs when coordinating multiple parallel analyses. It is necessary when your workflow requires consolidating findings from concurrent branches and preparing a single structured output for downstream nodes.

Can I validate aggregated DAG outputs before sending them to downstream nodes?▼

Yes, the aggregation process includes validation hooks for downstream nodes. After applying the merge strategy and conflict resolution, the output is formatted and validated to ensure the final consolidated result meets downstream requirements.

What is the best way to consolidate multiple parallel analyses into one structured result?▼

The best way to consolidate parallel analyses is using an aggregator that collects all branch outputs, applies a deep merge or priority strategy, tracks provenance for conflicts, and validates the final structured result for downstream consumption.