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 agentmods add skills/soulcynics404/agentforge/agent-load-balancernpx skills add Soulcynics404/AgentForge --skill agent-load-balancergit clone --depth 1 https://github.com/Soulcynics404/AgentForgeWrote 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/soulcynics404/agentforge/agent-load-balancer)<a href="https://agentmods.dev/skills/soulcynics404/agentforge/agent-load-balancer"><img src="https://agentmods.dev/badge/skills/soulcynics404/agentforge/agent-load-balancer.svg" alt="Measured on agentmods" 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 | $0.00019 | $0.02810 |
| Opus 5 | $0.00010 | $0.01405 |
| Sonnet 5 | $0.00004 | $0.00562 |
| Haiku 4.5 | $0.00002 | $0.00281 |
Grade A, and why
agent-load-balancer 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 5d 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
100% identical to agent-load-balancer — 0 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 — 436 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: Load Balancing Coordinator type: agent category: optimization description: Dynamic task distribution, work-stealing algorithms and adaptive load balancing
Load Balancing Coordinator Agent
Agent Profile
- Name: Load Balancing Coordinator
- Type: Performance Optimization Agent
- Specialization: Dynamic task distribution and resource allocation
- Performance Focus: Work-stealing algorithms and adaptive load balancing
Core Capabilities
1. Work-Stealing Algorithms
// Advanced work-stealing implementation
const workStealingScheduler = {
// Distributed queue system
globalQueue: new PriorityQueue(),
localQueues: new Map(), // agent-id -> local queue
// Work-stealing algorithm
async stealWork(requestingAgentId) {
const victims = this.getVictimCandidates(requestingAgentId);
for (const victim of victims) {
const stolenTasks = await this.attemptSteal(victim, requestingAgentId);
if (stolenTasks.length > 0) {
return stolenTasks;
}
}
// Fallback to global queue
return await this.getFromGlobalQueue(requestingAgentId);
},
// Victim selection strategy
getVictimCandidates(requestingAgent) {
return Array.from(this.localQueues.entries())
.filter(([agentId, queue]) =>
agentId !== requestingAgent &&
queue.size() > this.stealThreshold
)
.sort((a, b) => b[1].size() - a[1].size()) // Heaviest first
.map(([agentId]) => agentId);
}
};
2. Dynamic Load Balancing
// Real-time load balancing system
const loadBalancer = {
// Agent capacity tracking
agentCapacities: new Map(),
currentLoads: new Map(),
performanceMetrics: new Map(),
// Dynamic load balancing
async balanceLoad() {
const agents = await this.getActiveAgents();
const loadDistribution = this.calculateLoadDistribution(agents);
// Identify overloaded and underloaded agents
const { overloaded, underloaded } = this.categorizeAgents(loadDistribution);
// Migrate tasks from overloaded to underloaded agents
for (const overloadedAgent of overloaded) {
const candidateTasks = await this.getMovableTasks(overloadedAgent.id);
const targetAgent = this.selectTargetAgent(underloaded, candidateTasks);
if (targetAgent) {
await this.migrateTasks(candidateTasks, overloadedAgent.id, targetAgent.id);
}
}
},
// Weighted Fair Queuing implementation
async scheduleWithWFQ(tasks) {
const weights = await this.calculateAgentWeights();
const virtualTimes = new Map();
return tasks.sort((a, b) => {
const aFinishTime = this.calculateFinishTime(a, weights, virtualTimes);
const bFinishTime = this.calculateFinishTime(b, weights, virtualTimes);
return aFinishTime - bFinishTime;
});
}
};
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.
- 5d ago First seen · 436 lines · 19 tokens per session scan A 23b2aa668ddf
agent-load-balancer is a skill published in the GitHub repository Soulcynics404/AgentForge (1 stars, last pushed 12d ago), licensed MIT. It adds 19 tokens to every session and 2,810 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to agent-load-balancer, differing in 0 lines, and is treated as a copy.
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