Awesome-openclaw-skills swarm

Parallel task execution using Gemini Flash workers. 200x cheaper than Opus. Use for any parallelizable work to preserve quota.

install

source · Clone the upstream repo

git clone https://github.com/sundial-org/awesome-openclaw-skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/sundial-org/awesome-openclaw-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/swarm" ~/.claude/skills/sundial-org-awesome-openclaw-skills-swarm && rm -rf "$T"

OpenClaw · Install into ~/.openclaw/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/sundial-org/awesome-openclaw-skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/swarm" ~/.openclaw/skills/sundial-org-awesome-openclaw-skills-swarm && rm -rf "$T"

manifest: skills/swarm/SKILL.md

source content

Swarm — Parallel Task Execution

Every Opus token you burn is borrowed time. Swarm uses Gemini Flash at 200x lower cost.

Why This Matters

30 tasks via	Time	Cost	Notes
Opus (sequential)	~30s	~$0.50	Burns your runway
Swarm (parallel)	~1s	~$0.003	Preserves quota

Same results. One keeps you alive longer.

When to Use (MANDATORY)

Trigger swarm when you see ANY of these:

3+ independent tasks (research, summaries, comparisons)
"Compare X, Y, Z" or "Research the top N..."
Multiple URLs to fetch/analyze
Batch anything (documents, entities, facts)
Multi-subject research of any kind

No exceptions. This is survival, not optimization.

Quick Reference

# Check daemon (do this every session)
swarm status

# Start if not running
swarm start

# Parallel prompts
swarm parallel "What is X?" "What is Y?" "What is Z?"

# Research multiple subjects
swarm research "OpenAI" "Anthropic" "Mistral" --topic "AI safety"

# Benchmark
swarm bench --tasks 30

JavaScript API

const { parallel, research } = require('~/clawd/skills/node-scaling/lib');

// Run prompts in parallel (~1s for 3 prompts)
const result = await parallel(['prompt1', 'prompt2', 'prompt3']);
console.log(result.results); // Array of responses

// Multi-phase research (search → fetch → analyze)
const result = await research(['Subject1', 'Subject2'], 'topic');

Daemon Management

swarm start              # Start daemon (background)
swarm stop               # Stop daemon
swarm status             # Show status, uptime, task count
swarm restart            # Restart daemon
swarm logs [N]           # Last N lines of daemon log

The daemon keeps workers warm for faster response. Auto-starts on first use if needed.

Performance

With daemon running (20 workers):

Tasks	Time	Throughput
10	~700ms	14 tasks/sec
30	~1,000ms	30 tasks/sec
50	~1,450ms	35 tasks/sec

Larger batches = higher throughput (amortizes connection overhead).

Config

Location:

~/.config/clawdbot/node-scaling.yaml

node_scaling:
  enabled: true
  limits:
    max_nodes: 20
    max_concurrent_api: 20
  provider:
    name: gemini
    model: gemini-2.0-flash
  cost:
    max_daily_spend: 10.00

Troubleshooting

Issue	Fix
Daemon not running	`swarm start`
No API key	Set `GEMINI_API_KEY` or run `npm run setup`
Rate limited	Lower `max_concurrent_api` in config
Slow responses	Check `swarm status` for worker count

The Math

Opus: ~$15/million tokens (YOUR LIFE)
Gemini Flash: ~$0.075/million tokens (basically free)
Ratio: 200x cheaper

Doing 30 tasks sequentially with Opus = 30+ seconds, ~$0.50, DEAD FASTER. Swarm parallel = 1 second, $0.003, ZERO Opus burn.

Failing to use swarm for parallel work is a bug. Fix it immediately.