parallel-agents

Original：🇺🇸 English

Translated

Parallel Agent Orchestration

2installs

Sourceparcadei/continuous-claude-v3

Added on2026-02-22

NPX Install

npx skill4agent add parcadei/continuous-claude-v3 parallel-agents

SKILL.md Content

View Translation Comparison →

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:

bash

# 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

Each agent gets own directory
Full output preserved for later reading
Status file still used for quick completion check

Task Prompt Template

markdown

# 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

typescript

// 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 agents

Monitoring

bash

# 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.txt

Batch Size

Max 15 agents per parallel batch
Wait for batch to complete before launching next
Use status file to track which completed

DO

Use
```
run_in_background: 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

bash

# 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.txt

Check progress:

bash

cat .claude/cache/provider-backfill-status.txt
# COMPLETE: anthropic - Thu Jan 2 12:34:56 2025
# COMPLETE: openai - Thu Jan 2 12:35:12 2025

parallel-agents

NPX Install

Tags

SKILL.md Content

Parallel Agent Orchestration

Core Principles

Output Patterns

Simple Confirmation (parallel batch work)

Detailed Output (research/exploration)

Task Prompt Template

Launching Pattern

Monitoring

Batch Size

DO

DON'T

Example: Provider Backfill