Parallel Agents

This is a pattern for running up to 15 agents in parallel without destroying your context window. The key insight: don't use TaskOutput to check on agents because it dumps their entire output into context. Instead, have each agent append a completion line to a shared status file, then read that file to see who's done. Agents run with run_in_background: true and write "COMPLETE: task-name" when finished. For tasks that need more than just confirmation, each agent gets its own directory under .claude/cache/agents/. It's simple but solves a real problem if you're orchestrating batch work like backfilling data across providers or running parallel research tasks.

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last updated: Aug 21, 2026

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Install

$ npx -y skills add parcadei/continuous-claude-v3 --skill parallel-agents --agent claude-code

Installs into .claude/skills of the current project.

Files

Parallel Agent Orchestration

When launching multiple agents in parallel, follow this pattern to avoid context bloat.

Core Principles

No TaskOutput calls - TaskOutput returns full agent output, bloating context
Run in background - Always use run_in_background: true
File-based confirmation - Agents write status to files, not return values
Append, don't overwrite - Multiple agents can write to same status file

Output Patterns

Simple Confirmation (parallel batch work)

For tasks where agents just need to confirm completion:

# Agent writes to shared status file
echo "COMPLETE: <task-name> - $(date)" >> .claude/cache/<batch-name>-status.txt

Use >> to append (not > which overwrites)
Include timestamp for ordering
One line per agent completion
Check with: cat .claude/cache/<batch-name>-status.txt

Detailed Output (research/exploration)

For tasks requiring detailed findings:

.claude/cache/agents/<task-type>/<agent-id>/
├── output.md      # Main findings
├── artifacts/     # Any generated files
└── status.txt     # Completion confirmation

SKILL.md on GitHub