Multi-Agent Orchestration for Context Isolation Skill

Multi-Agent Orchestration for Context Isolation

Implements Orchestrator, Swarm, and Hierarchical patterns.

The Three Orchestration Patterns

1. Orchestrator Pattern (Task Delegation)

When to Use:

Single complex task requiring different expertise areas
Need to prevent main agent context saturation
Tasks have clear sub-components that can be parallelized
Want centralized planning with distributed execution

2. Swarm Pattern (Parallel Execution)

When to Use:

Multiple independent tasks of same type
Need for parallel speedup
Different perspectives on same problem
Large-scale data processing

3. Hierarchical Pattern (Supervision)

When to Use:

Large, complex tasks with hierarchy
Need for quality control
Multi-level task decomposition
Quality gates required

Pattern Selection Guide

Decision Matrix

| Use Case | Orchestrator | Swarm | Hierarchical | |----------|--------------|-------|--------------| | Task Decomposition | Best | Possible | Good | | Parallel Execution | Limited | Best | Possible | | Quality Control | Limited | No | Best | | Scalability | Medium | High | High | | Complexity | Medium | Low | High |

Selection Criteria

Choose Orchestrator when: Clear task decomposition available, need centralized coordination, different expertise areas required, single complex task

Choose Swarm when: Multiple independent tasks, parallel speedup needed, different perspectives helpful, large-scale processing

Choose Hierarchical when: Quality control critical, multi-level tasks, need supervision at each level, complex error handling required

Context Isolation Principles

The Solution: Context Isolation

Rule 1: Specialized Contexts - Each agent has focused context, only task-relevant information, no cross-agent contamination

Rule 2: Minimal Exchange - Pass only necessary data, use structured formats, avoid conversation history sharing

Rule 3: Results, Not Context - Agents return results, not ongoing context, synthesize results centrally, maintain global view in orchestrator

Advanced Context Isolation Strategies

Context Degradation Patterns

| Pattern | Symptom | Mitigation | |:--------|:--------|:-----------| | Lost-in-Middle | Info at 40-60% position ignored | Place critical info at start/end | | Context Poisoning | Errors compound through references | Require source citations | | Context Distraction | Model ignores training knowledge | Quality over quantity | | Context Confusion | Incorrect associations | Rigorous context selection | | Context Clash | Contradictory information | Establish information hierarchy |

Context Isolation Techniques

1. TodoWrite Attention Manipulation (Recitation)

Constantly rewrite todos to push objectives into recent attention span:

# Update after every major tool call
## Phase 1: Research
- [x] Analyze codebase structure
- [ ] Identify patterns  ← Visible in recent attention
- [ ] Plan implementation

Why It Works:

Todo rewriting recites objectives into context end

2. System Reminders

Combat degradation through recurring objective injection:

Effective Patterns:

Objective recitation - Reiterate main goal
Constraint reinforcement - Re-emphasize requirements
Context anchoring - Reference key elements

3. Plan Mode Coordination

Use plan mode for complex, multi-phase tasks:

When to Use:

Complex tasks requiring 10+ tool calls
Multi-phase implementations
When agent appears confused or drifting

Best Practices:

Create plan at task start
Update as understanding evolves
Reference plan in reminders
Store in .cattoolkit/context/plan.md

Context Window Thresholds & Actions

| Utilization | Action | Technique | |:------------|:-------|:----------| | <60% | Monitor | No action needed | | 60-80% | Light compression | Observation masking | | 80-95% | Aggressive compression | Summarization + compaction | | >95% | Emergency | Force session handoff |

Best Practices

Recommended Practices

Define Clear Interfaces - Specify input/output formats, use structured data, document expectations

Minimize Context Sharing - Pass only necessary data, avoid conversation history, use file-based coordination

Isolate Agent Contexts - Each agent focused on specific task, no cross-contamination, specialized expertise

Return Results, Not Context - Agents produce artifacts, structured outputs, central synthesis

Test Isolation - Verify agents don't share context, check result quality, validate coordination

Use Progressive Context Loading - Load only what's needed when needed

Apply Attention Management - Use TodoWrite, reminders, and plan mode strategically

Practices to Avoid

Sharing Full Context - Never pass conversation history, don't share unrelated information, maintain isolation

Over-Complicating - Start simple, add complexity incrementally, use appropriate pattern

Ignoring Coordination - Plan result merging, handle conflicts, manage dependencies

Violating Isolation - Keep contexts separate, use file-based coordination, respect boundaries

Ignoring Degradation - Monitor context utilization, apply compression early

Reference Materials

Core Patterns:

See: orchestrator-pattern.md - Complete orchestrator implementation guide
See: swarm-pattern.md - Complete swarm implementation guide
See: hierarchical-pattern.md - Complete hierarchical implementation guide

Implementation:

See: implementation-guide.md - Step-by-step implementation
See: context-isolation.md - Context management strategies
See: coordination.md - Agent coordination patterns

Next Steps

Assess Requirements - Task complexity, parallelism needs, quality requirements
Choose Pattern - Use decision matrix, consider constraints, match use case
Design Architecture - Define agent roles, plan context isolation, specify interfaces
Implement Incrementally - Start simple, add complexity, test isolation
Monitor and Optimize - Measure performance, check quality, optimize bottlenecks

Agent Skills: Multi-Agent Orchestration for Context Isolation

Install this agent skill to your local

Skill Files