research-orchestration

Parallel research agent orchestration dispatching 5-10 concurrent agents for comprehensive multi-source research with synthesis and validation.

509 stars

Best use case

research-orchestration is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Parallel research agent orchestration dispatching 5-10 concurrent agents for comprehensive multi-source research with synthesis and validation.

Teams using research-orchestration should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/research-orchestration/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/methodologies/claudekit/skills/research-orchestration/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/research-orchestration/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How research-orchestration Compares

Feature / Agentresearch-orchestrationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Parallel research agent orchestration dispatching 5-10 concurrent agents for comprehensive multi-source research with synthesis and validation.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Research Orchestration

## Overview

Orchestrates 5-10 parallel research agents for comprehensive, multi-source research. Achieves up to 90% faster results compared to sequential research through concurrent execution.

## Research Depths

| Depth | Agent Count | Use Case |
|-------|------------|----------|
| Shallow | 5 | Quick fact-finding, simple queries |
| Medium | 7 | Standard research, moderate complexity |
| Deep | 10 | Comprehensive analysis, complex queries |

## Process Flow

1. **Plan**: Decompose query into independent sub-queries
2. **Dispatch**: Run 5-10 research agents in parallel
3. **Synthesize**: Merge findings, identify consensus and conflicts
4. **Validate**: Cross-reference against codebase for accuracy

## Sources

- Codebase: source files, patterns, implementations
- Documentation: README, JSDoc, inline comments
- Configuration: package.json, tsconfig, CI/CD configs

## Confidence Scoring

Overall confidence is a weighted average of individual agent confidence scores, adjusted by validation results. Below 70% triggers human review.

## When to Use

- `/research [query]` slash command
- Before specification creation
- When investigating unfamiliar parts of the codebase

## Processes Used By

- `claudekit-research` (primary consumer)

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