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 Quinoto-Tech/QuinotoSpec --skill quinotospec-battle-frenzygit clone --depth 1 https://github.com/Quinoto-Tech/QuinotoSpecWrote 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/quinoto-tech/quinotospec/quinotospec-battle-frenzy)<a href="https://agentmods.dev/skills/quinoto-tech/quinotospec/quinotospec-battle-frenzy"><img src="https://agentmods.dev/badge/skills/quinoto-tech/quinotospec/quinotospec-battle-frenzy/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/quinoto-tech/quinotospec/quinotospec-battle-frenzy"><img src="https://agentmods.dev/badge/skills/quinoto-tech/quinotospec/quinotospec-battle-frenzy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00021 | $0.00988 |
| Opus 5 | $0.00010 | $0.00494 |
| Sonnet 5 | $0.00004 | $0.00198 |
| Haiku 4.5 | $0.00002 | $0.00099 |
Grade A, and why
quinotospec-battle-frenzy 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Battle Frenzy: Swarm Mode
Ejecuta múltiples subagentes en paralelo para tareas masivas.
Concepto
Battle Frenzy divide tareas grandes en chunks independientes y los ejecuta en paralelo:
- Analiza la tarea y determina si es paralelizable
- Divide en chunks de hasta 5 trabajadores simultáneos
- Ejecuta usando subagentes en paralelo
- Consolida resultados
Comandos
| Comando | Descripción |
|---|---|
@quinotospec.battle-frenzy |
Ejecución completa |
@quinotospec.battle-frenzy --dry-run |
Solo mostrar división |
@quinotospec.battle-frenzy --limit N |
Limitar a N agentes |
Flujo de Ejecución
Paso 1 — Task Splitter
Ejecutar skill quinotospec-swarm-task-splitter:
- Analiza la tarea masiva
- Determina si es paralelizable
- Genera
chunks.jsoncon chunks independientes
Paso 2 — Validación
Si --dry-run: mostrar chunks y preguntar confirmar
Paso 3 — Swarm Executor
Ejecutar skill quinotospec-swarm-executor:
- Lee
chunks.json - Agrupa chunks por dependencias (waves)
- Ejecuta en paralelo (max 5)
- Recolecta resultados
Paso 4 — Consolidación
Combinar resultados y generar reporte:
- Mostrar summary
- Detallar éxitos y fallos
- Ofrecer siguiente acción
Paso 5 — Changelog (OBLIGATORIO, salvo --dry-run)
Si NO se ejecutó con --dry-run (es decir, si hubo ejecución real de chunks), DEBES ejecutar la skill quinotospec-update-changelog.
- Título de la Acción: Battle Frenzy Ejecutado: {{TAREA_ORIGINAL}}
- Resumen: Se ejecutaron {{N}} chunks en paralelo ({{WAVES}} waves). Resultado: {{EXITOSOS}}/{{N}} exitosos. Reporte en
.quinoto-spec/swarm/results.json.
Si se ejecutó con --dry-run, omite este paso — no hubo cambios reales.
Ejemplo de Sesión
👤: @quinotospec.battle-frenzy Migrar 10 endpoints a v2
🤖: 🪓 **Battle Frenzy: Análisis**
Analizando tarea: Migrar 10 endpoints a v2
¿Es paralelizable? ✅ Sí (independientes)
Dividiendo en chunks...
→ SWARM-001: /users
→ SWARM-002: /products
→ SWARM-003: /orders
→ SWARM-004: /payments
→ SWARM-005: /notifications
→ SWARM-006: /auth
→ SWARM-007: /profile
→ SWARM-008: /settings
→ SWARM-009: /reports
→ SWARM-010: /webhooks
Total: 10 chunks, 5 paralelos, 2 waves
⚡ Ejecutando en paralelo...
Wave 1: [SWARM-001 al SWARM-005] → ✅✅✅✅✅
Wave 2: [SWARM-006 al SWARM-010] → ✅✅✅✅✅
🪓 **Battle Frenzy: Completado**
✅ 10/10 exitosos (45s)
📊 Reporte: .quinoto-spec/swarm/results.json
👤: @quinotospec.battle-frenzy --dry-run
🤖: 🪓 **Battle Frenzy: Dry Run**
Chunks generados (no ejecutados):
├── SWARM-001: /users
├── SWARM-002: /products
└── ...
Para ejecutar: @quinotospec.battle-frenzy
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 Changed · +7 lines d1ea15bb639c
- 12d ago First seen · 119 lines · 21 tokens per session scan A b369451bd538
quinotospec-battle-frenzy is a skill published in the GitHub repository Quinoto-Tech/QuinotoSpec (20 stars, last pushed today), licensed MIT. It adds 21 tokens to every session and 988 once invoked, about $0.0001 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 2026-08-30.
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