Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ayushcodes10/echo-mem --skill swarm-orchestrationgit clone --depth 1 https://github.com/ayushcodes10/echo-memWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ayushcodes10/echo-mem/swarm-orchestration)<a href="https://agentmods.dev/skills/ayushcodes10/echo-mem/swarm-orchestration"><img src="https://agentmods.dev/badge/skills/ayushcodes10/echo-mem/swarm-orchestration/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ayushcodes10/echo-mem/swarm-orchestration"><img src="https://agentmods.dev/badge/skills/ayushcodes10/echo-mem/swarm-orchestration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00046 | $0.01053 |
| Opus 5.5 | $0.00018 | $0.00421 |
| Sonnet 5.5 | $0.00009 | $0.00211 |
| Haiku 4.5 | $0.00005 | $0.00105 |
Grade A, and why
Swarm Orchestration scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
95% identical to Swarm Orchestration — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Swarm Orchestration
What This Skill Does
Orchestrates multi-agent swarms using agentic-flow's advanced coordination system. Supports mesh, hierarchical, and adaptive topologies with automatic task distribution, load balancing, and fault tolerance.
Prerequisites
- agentic-flow v1.5.11+
- Node.js 18+
- Understanding of distributed systems (helpful)
Quick Start
# Initialize swarm
npx agentic-flow hooks swarm-init --topology mesh --max-agents 5
# Spawn agents
npx agentic-flow hooks agent-spawn --type coder
npx agentic-flow hooks agent-spawn --type tester
npx agentic-flow hooks agent-spawn --type reviewer
# Orchestrate task
npx agentic-flow hooks task-orchestrate \
--task "Build REST API with tests" \
--mode parallel
Topology Patterns
1. Mesh (Peer-to-Peer)
// Equal peers, distributed decision-making
await swarm.init({
topology: 'mesh',
agents: ['coder', 'tester', 'reviewer'],
communication: 'broadcast'
});
2. Hierarchical (Queen-Worker)
// Centralized coordination, specialized workers
await swarm.init({
topology: 'hierarchical',
queen: 'architect',
workers: ['backend-dev', 'frontend-dev', 'db-designer']
});
3. Adaptive (Dynamic)
// Automatically switches topology based on task
await swarm.init({
topology: 'adaptive',
optimization: 'task-complexity'
});
Task Orchestration
Parallel Execution
// Execute tasks concurrently
const results = await swarm.execute({
tasks: [
{ agent: 'coder', task: 'Implement API endpoints' },
{ agent: 'frontend', task: 'Build UI components' },
{ agent: 'tester', task: 'Write test suite' }
],
mode: 'parallel',
timeout: 300000 // 5 minutes
});
Pipeline Execution
// Sequential pipeline with dependencies
await swarm.pipeline([
{ stage: 'design', agent: 'architect' },
{ stage: 'implement', agent: 'coder', after: 'design' },
{ stage: 'test', agent: 'tester', after: 'implement' },
{ stage: 'review', agent: 'reviewer', after: 'test' }
]);
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 180 lines · 46 tokens per session scan A 9f0bc14c44ec
Swarm Orchestration is a skill published in the GitHub repository ayushcodes10/echo-mem (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 46 tokens to every session and 1,053 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 95% identical to Swarm Orchestration, differing in 2 lines, and is treated as a copy.
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