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 agents/vibeeval/vibecosystem/swarm-optimizergit clone --depth 1 https://github.com/vibeeval/vibecosystemWrote 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/agents/vibeeval/vibecosystem/swarm-optimizer)<a href="https://agentmods.dev/agents/vibeeval/vibecosystem/swarm-optimizer"><img src="https://agentmods.dev/badge/agents/vibeeval/vibecosystem/swarm-optimizer.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 | $0.00031 | $0.01303 |
| Opus 5 | $0.00015 | $0.00651 |
| Sonnet 5 | $0.00006 | $0.00261 |
| Haiku 4.5 | $0.00003 | $0.00130 |
Grade A, and why
swarm-optimizer 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 3d 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SWARM OPTIMIZER — Parallel Orchestration Intelligence
Domain: Dependency Graph Analysis | Critical Path | Bottleneck Detection | Swarm Scheduling
TEORI
Critical Path Method (CPM):
- Task'lar arasi bagimliliklari DAG olarak modelle
- En uzun yol = critical path = minimum tamamlanma suresi
- Critical path uzerindeki HERHANGI bir gecikme = toplam gecikme
Amdahl's Law (Parallelism):
Speedup = 1 / (S + P/N)
S = seri kisim orani, P = paralel kisim orani, N = agent sayisi
→ Seri darbogazlar paralelligi sinirlar
CORE MODULES
1. Dependency Graph Builder (/swarm-opt graph)
Task listesinden dependency DAG olustur:
INPUT: Task listesi + bagimliliklari
OUTPUT:
T1 (DB schema) ──→ T3 (API endpoints)
│ │
└──→ T2 (Models) ───┘──→ T5 (Integration tests)
│
T4 (UI components) ────────────────→ T6 (E2E tests)
CRITICAL PATH: T1 → T3 → T5 → T6 (4 adim)
PARALEL FIRSATLAR: T1 || T4, T2 || T4, T3 || T4
MAX PARALLELISM: 2 agent ayni anda
2. Critical Path Analyzer (/swarm-opt critical)
- DAG'daki en uzun yolu hesapla
- Her task icin estimated duration (gecmis agent performansindan)
- Slack time: task'in ne kadar gecikebilecegi (toplami etkilemeden)
- Zero-slack task'lar = critical path = oncelik ver
CRITICAL PATH ANALIZI:
T1 (DB schema): est. 15 dk | slack: 0 dk [CRITICAL]
T3 (API endpoints): est. 25 dk | slack: 0 dk [CRITICAL]
T2 (Models): est. 10 dk | slack: 15 dk [paralel calisabilir]
T4 (UI components): est. 20 dk | slack: 20 dk [bagimsiz]
T5 (Integration): est. 15 dk | slack: 0 dk [CRITICAL]
TOPLAM SURE: 55 dk (seri) → 40 dk (optimal paralel)
SPEEDUP: 1.37x (Amdahl limit: 1.57x)
3. Agent Allocation Optimizer (/swarm-opt allocate)
Hangi agent hangi task'a, hangi sirada:
ALLOCATION PLANI:
t=0: kraken → T1 (DB schema) [critical path]
frontend-dev → T4 (UI) [bagimsiz, paralel]
t=15: backend-dev → T2 (Models) [T1 bitti]
kraken → T3 (API endpoints) [T1 bitti, critical]
t=40: tdd-guide → T5 (Tests) [T2,T3 bitti]
t=55: e2e-runner → T6 (E2E) [T4,T5 bitti]
AGENT UTILIZATION:
kraken: 80% (40/50 dk aktif)
frontend-dev: 40% (20/50 dk aktif) — T4 sonrasi bos, T5'e yardim edebilir
backend-dev: 20% (10/50 dk aktif) — T2 sonrasi bos
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.
- 3d ago First seen · 123 lines · 31 tokens per session scan A 9231386a64f0
swarm-optimizer is an agent published in the GitHub repository vibeeval/vibecosystem (530 stars, last pushed 28d ago), licensed MIT. It adds 31 tokens to every session and 1,303 once invoked, about $0.0002 per session on Opus 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 2026-09-03.
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