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 source-command-swarm-optimizationgit 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/source-command-swarm-optimization)<a href="https://agentmods.dev/skills/ayushcodes10/echo-mem/source-command-swarm-optimization"><img src="https://agentmods.dev/badge/skills/ayushcodes10/echo-mem/source-command-swarm-optimization/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/source-command-swarm-optimization"><img src="https://agentmods.dev/badge/skills/ayushcodes10/echo-mem/source-command-swarm-optimization.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 | $0.00017 | $0.00680 |
| Opus 5.5 | $0.00007 | $0.00272 |
| Sonnet 5.5 | $0.00003 | $0.00136 |
| Haiku 4.5 | $0.00002 | $0.00068 |
Grade A, and why
source-command-swarm-optimization 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.
How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
source-command-swarm-optimization
Use this skill when the user asks to run the migrated source command swarm-optimization.
Command Template
Optimization Swarm Strategy
Purpose
Performance optimization through specialized analysis.
Activation
Using MCP Tools
// Initialize optimization swarm
mcp__claude-flow__swarm_init({
"topology": "mesh",
"maxAgents": 6,
"strategy": "adaptive"
})
// Orchestrate optimization task
mcp__claude-flow__task_orchestrate({
"task": "optimize performance",
"strategy": "parallel",
"priority": "high"
})
Using CLI (Fallback)
npx Codex-flow swarm "optimize performance" --strategy optimization
Agent Roles
Agent Spawning with MCP
// Spawn optimization agents
mcp__claude-flow__agent_spawn({
"type": "optimizer",
"name": "Performance Profiler",
"capabilities": ["profiling", "bottleneck-detection"]
})
mcp__claude-flow__agent_spawn({
"type": "analyst",
"name": "Memory Analyzer",
"capabilities": ["memory-analysis", "leak-detection"]
})
mcp__claude-flow__agent_spawn({
"type": "optimizer",
"name": "Code Optimizer",
"capabilities": ["code-optimization", "refactoring"]
})
mcp__claude-flow__agent_spawn({
"type": "tester",
"name": "Benchmark Runner",
"capabilities": ["benchmarking", "performance-testing"]
})
Optimization Areas
Performance Analysis
// Analyze bottlenecks
mcp__claude-flow__bottleneck_analyze({
"component": "all",
"metrics": ["cpu", "memory", "io", "network"]
})
// Run benchmarks
mcp__claude-flow__benchmark_run({
"suite": "performance"
})
// WASM optimization
mcp__claude-flow__wasm_optimize({
"operation": "simd-acceleration"
})
Optimization Operations
// Optimize topology
mcp__claude-flow__topology_optimize({
"swarmId": "optimization-swarm"
})
// DAA optimization
mcp__claude-flow__daa_optimization({
"target": "performance",
"metrics": ["speed", "memory", "efficiency"]
})
// Load balancing
mcp__claude-flow__load_balance({
"swarmId": "optimization-swarm",
"tasks": optimizationTasks
})
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 · 129 lines · 17 tokens per session scan A 79240ee79b97
source-command-swarm-optimization is a skill published in the GitHub repository ayushcodes10/echo-mem (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 17 tokens to every session and 680 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-12.
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