quinotospec-battle-frenzy

quinotospec-battle-frenzy is a skill for Claude Code, Codex from Quinoto-Tech/QuinotoSpec. It costs 21 tokens per session (988 once invoked), scanned A, original, MIT.

A workflow for splitting a large coding task into independent pieces and running several subagents at the same time. It groups dependent pieces into waves and combines their results into a report.

In plain words
What is it for?
Use it for tasks that can be divided into separate chunks, such as bulk code changes or analysis. You can preview the chunks or limit how many agents run concurrently.
Why use it?
It reduces the need to handle a large batch of similar work one piece at a time. A dry-run mode lets you inspect the proposed split before execution.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it for tasks that can be divided into separate chunks, such as bulk code changes or analysis. You can preview the chunks or limit how many agents run concurrently.

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Install with agentmods
npx agentmods add skills/quinoto-tech/quinotospec/quinotospec-battle-frenzy
Install

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.

Any agent
npx skills add Quinoto-Tech/QuinotoSpec --skill quinotospec-battle-frenzy
Clone the repo
git clone --depth 1 https://github.com/Quinoto-Tech/QuinotoSpec

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for quinotospec-battle-frenzy

README.md
[![agentmods](https://agentmods.dev/badge/skills/quinoto-tech/quinotospec/quinotospec-battle-frenzy/github.svg)](https://agentmods.dev/skills/quinoto-tech/quinotospec/quinotospec-battle-frenzy)
Your own site
<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.

agentmods 80×15 button for quinotospec-battle-frenzy

Your own site · 80×15
<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>
Per session 21 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 988 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 3d ago against content hash d1ea15bb639c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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.

agent-dist/skills/quinotospec-battle-frenzy/SKILL.md · 126 lines

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.json con 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

Read the full file on GitHub · 126 lines

Changes

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.

  1. 3d ago Changed · +7 lines d1ea15bb639c
  2. 12d ago First seen · 119 lines · 21 tokens per session scan A b369451bd538

Subscribe to this mod's changes

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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