parallel-agents skill
Parallel Agent Orchestration
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Install the parallel-agents skill
A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.
git clone --depth 1 https://github.com/parcadei/Continuous-Claude-v3.git /tmp/Continuous-Claude-v3 mkdir -p ~/.claude/skills cp -r /tmp/Continuous-Claude-v3/.claude/skills/parallel-agents ~/.claude/skills/parallel-agents
available in every project
In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub
The instructions your agent would load
SKILL.md as published, without the frontmatter. Read it on GitHub
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 runinbackground: 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/-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- Each agent gets own directory
- Full output preserved for later reading
- Status file still used for quick completion check
Task Prompt Template
# Task: <TASK_NAME>
## Your Mission
<clear objective>
## Output
When done, write confirmation:
\`\`\`bash
echo "COMPLETE: <identifier> - $(date)" >> .claude/cache/<batch>-status.txt
\`\`\`
Do NOT return large output. Complete work silently.Launching Pattern
// Launch all in single message block (parallel)
Task({
description: "Task 1",
prompt: "...",
subagent_type: "general-purpose",
run_in_background: true
})
Task({
description: "Task 2",
prompt: "...",
subagent_type: "general-purpose",
run_in_background: true
})
// ... up to 15 parallel agentsMonitoring
# Check completion status
cat .claude/cache/<batch>-status.txt
# Count completions
wc -l .claude/cache/<batch>-status.txt
# Watch for updates
tail -f .claude/cache/<batch>-status.txtBatch Size
- Max 15 agents per parallel batch
- Wait for batch to complete before launching next
- Use status file to track which completed
DO
- Use runinbackground: true always
- Have agents write to status files
- Use append (>>) not overwrite (>)
- Give each agent clear, self-contained instructions
- Include all context in prompt (agents don't share memory)
DON'T
- Call TaskOutput (bloats context)
- Return large outputs from agents
- Launch more than 15 at once
- Rely on agent return values for orchestration
Example: Provider Backfill
# Status file
.claude/cache/provider-backfill-status.txt
# Each agent appends on completion
echo "COMPLETE: anthropic - Thu Jan 2 12:34:56 2025" >> .claude/cache/provider-backfill-status.txt
echo "COMPLETE: openai - Thu Jan 2 12:35:12 2025" >> .claude/cache/provider-backfill-status.txtCheck progress:
cat .claude/cache/provider-backfill-status.txt
# COMPLETE: anthropic - Thu Jan 2 12:34:56 2025
# COMPLETE: openai - Thu Jan 2 12:35:12 2025More skills from parcadei/Continuous-Claude-v3
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