parallel-agents

parcadei/continuous-claude-v3 · updated Apr 8, 2026

$npx skills add https://github.com/parcadei/continuous-claude-v3 --skill parallel-agents
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summary

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

skill.md

Parallel Agent Orchestration

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

Core Principles

  1. No TaskOutput calls - TaskOutput returns full agent output, bloating context
  2. Run in background - Always use run_in_background: true
  3. File-based confirmation - Agents write status to files, not return values
  4. 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
  • 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 agents

Monitoring

# 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

# 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:

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

Discussion

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general reviews

Ratings

4.543 reviews
  • Yusuf Torres· Dec 28, 2024

    Registry listing for parallel-agents matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Chinedu Huang· Dec 16, 2024

    Keeps context tight: parallel-agents is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Chaitanya Patil· Dec 8, 2024

    Useful defaults in parallel-agents — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Chinedu Diallo· Dec 8, 2024

    parallel-agents has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Piyush G· Nov 27, 2024

    parallel-agents is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Fatima Smith· Nov 19, 2024

    parallel-agents fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Ama Gonzalez· Oct 26, 2024

    Useful defaults in parallel-agents — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Shikha Mishra· Oct 18, 2024

    Keeps context tight: parallel-agents is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Kiara Diallo· Oct 10, 2024

    We added parallel-agents from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Fatima Mensah· Sep 21, 2024

    Useful defaults in parallel-agents — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

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