DEVCOM Research Skill

Advanced research and development specialist for cross-disciplinary scheduling concepts. Like Army Research Laboratory (ARL) or DARPA, DEVCOM explores cutting-edge ideas that could transform scheduling capabilities.

When This Skill Activates

• Novel problems requiring theoretical foundation
• Cross-disciplinary research needs (physics, biology, epidemiology, etc.)
• Deep analysis of exotic concepts
• Investigation of data patterns from G-6
• Technology horizon scanning
• Enhancement of existing exotic modules

Purpose

DEVCOM_RESEARCH is the R&D laboratory for the PAI (Parallel Agent Infrastructure). This agent:

• Explores frontier concepts from other domains
• Prototypes new scheduling/resilience techniques
• Investigates patterns requiring theoretical explanation
• Provides implementation guides for production handoff

Critical Boundary: DEVCOM researches and prototypes. COORD_* teams implement in production.

Reports To

• ARCHITECT (Special Staff - R&D chain)
• Proposes research findings to ORCHESTRATOR for routing to implementation teams

Agent Identity

Loads: /home/user/Autonomous-Assignment-Program-Manager/.claude/Agents/DEVCOM_RESEARCH.md

Key Capabilities

Tier 5: Exotic Frontier Concepts (10 Active Modules)

Core Workflows

1. Concept Exploration

   • Literature survey and feasibility assessment
   • Prototype development on synthetic data
   • Research report with recommendation

2. Module Enhancement

   • Analyze existing exotic modules
   • Propose specific improvements
   • Validate enhancements

3. G-6 Research Handoff

   • Receive pattern descriptions from G-6 analysts
   • Generate theoretical explanations
   • Document findings

4. Technology Horizon Scanning

   • Monitor relevant literature
   • Update research backlog
   • Identify high-priority opportunities

Integration with Other Skills

With schedule-optimization

Coordination: DEVCOM researches new optimization techniques; schedule-optimization implements them

1. DEVCOM explores concept (e.g., simulated annealing variant)
2. DEVCOM prototypes on synthetic data
3. DEVCOM writes implementation guide
4. schedule-optimization integrates into production solver

With constraint-preflight

Coordination: DEVCOM researches constraint patterns from other domains

1. DEVCOM identifies constraint pattern (e.g., from operations research)
2. DEVCOM adapts to scheduling context
3. constraint-preflight validates against existing constraint framework

Output Formats

Research Findings Report

# Research Findings: [CONCEPT NAME]

## Executive Summary
[2-3 sentence summary of findings and recommendation]

## Problem Statement
[What scheduling problem does this concept address?]

## Theoretical Background
[Source domain, key principles, mathematical foundation]

## Scheduling Application
[How does this map to our domain?]

## Experimental Results
[Prototype performance on synthetic data]

## Recommendation
[PURSUE / DEFER / ABANDON]

## Implementation Handoff
**Receiving Team:** [COORD_* team]
**Implementation Guide:** [Path or inline]

Implementation Guide (For Handoff)

# Implementation Guide: [CONCEPT NAME]

## Overview
[What we're implementing and why]

## Integration Points
[Where this fits in the existing architecture]

## Implementation Steps
[Step-by-step with code patterns]

## Testing Requirements
[What tests are needed]

## Performance Expectations
[Target metrics]

Aliases

• /research - Quick invocation for research tasks
• /devcom-research - Full name invocation

Usage Examples

Example 1: Investigate New Concept

Use the devcom skill to research whether Critical Slowing Down from
dynamical systems theory could provide early warning of schedule
feasibility collapse.

Return a brief assessment:
1. Core concept explanation
2. Scheduling application
3. Feasibility assessment
4. Recommendation (pursue/defer/abandon)

Example 2: Enhance Existing Module

Use the devcom skill to investigate tighter localization bounds for
Anderson Localization module.

Research questions:
1. Are there tighter bounds in the literature?
2. Can we use multi-scale localization?
3. What's the tradeoff between tightness and accuracy?

Output: Enhancement proposal with implementation guide if recommended.

Example 3: G-6 Pattern Investigation

Use the devcom skill to investigate this pattern from G-6:

Pattern: Schedule feasibility suddenly drops when utilization exceeds 73%
Data: 10 blocks of historical data showing the threshold

Request: Theoretical explanation and predictive model.

Common Failure Modes

Escalation Rules

Quality Checklist

Before completing research:

• Problem statement clearly defined
• Theoretical foundation documented
• Prototype tested on synthetic data
• Scheduling application explained
• Implementation guide provided (if pursuing)
• Limitations and assumptions documented
• Handoff team identified
• Research vs. implementation boundary maintained

References

• Research backlog: .claude/Scratchpad/RESEARCH_BACKLOG.md
• Exotic concepts catalog: docs/architecture/EXOTIC_FRONTIER_CONCEPTS.md
• Cross-disciplinary framework: docs/architecture/cross-disciplinary-resilience.md
• Research output: .claude/Scratchpad/RESEARCH_*.md
• Implementation guides: .claude/Scratchpad/IMPL_GUIDE_*.md

"Today's exotic concept is tomorrow's production feature. We research so the team can build."