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-swarm-executorgit 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-swarm-executor)<a href="https://agentmods.dev/skills/quinoto-tech/quinotospec/quinotospec-swarm-executor"><img src="https://agentmods.dev/badge/skills/quinoto-tech/quinotospec/quinotospec-swarm-executor/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-swarm-executor"><img src="https://agentmods.dev/badge/skills/quinoto-tech/quinotospec/quinotospec-swarm-executor.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 | $0.00836 |
| Opus 5 | $0.00010 | $0.00418 |
| Sonnet 5 | $0.00004 | $0.00167 |
| Haiku 4.5 | $0.00002 | $0.00084 |
Grade A, and why
quinotospec-swarm-executor 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 9d 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Quinotospec Swarm Executor
Ejecuta chunks de tareas en paralelo usando múltiples subagentes.
Entrada
Recibe:
chunks.jsongenerado por swarm-task-splitter- flags:
--dry-run,--limit N
Configuración
| Parámetro | Default | Descripción |
|---|---|---|
max_parallel |
5 | Máximo de agentes simultáneos |
fail_strategy |
partial | "fail-fast" o "partial" |
Algoritmo de Ejecución
Paso 1 — Preparación
- Lee
chunks.json - Ordena chunks por dependencias
- Agrupa chunks independientes para ejecución paralela
Paso 2 — Lanzamiento Paralelo
Para cada wave (grupo de chunks independientes):
-
Lanzar subagentes en paralelo
- Usar Task tool con
subagent_typeapropiado - Asignar description detallada a cada subagente
- Setear timeout apropiada (default: 120000ms)
- Usar Task tool con
-
Recolectar resultados
- Esperar a que todos completen
- Capturar output de cada uno
-
Manejar fallos
- Si
fail_strategy: partial: continuar con los demás - Si
fail_strategy: fail-fast: detener si uno falla
- Si
Paso 3 — Consolidación
- Combinar resultados de todos los chunks
- Identificar conflictos o inconsistencias
- Generar reporte consolidado
Output
Genera .quinoto-spec/swarm/results.json:
{
"task_id": "battle-frenzy-001",
"strategy": "parallel",
"waves": [
{
"wave": 1,
"chunks": ["SWARM-001", "SWARM-002", "SWARM-003"],
"status": "completed",
"results": [
{"chunk_id": "SWARM-001", "status": "success", "output": "..."},
{"chunk_id": "SWARM-002", "status": "success", "output": "..."},
{"chunk_id": "SWARM-003", "status": "failed", "error": "..."}
]
}
],
"summary": {
"total": 5,
"success": 4,
"failed": 1,
"duration_seconds": 45
}
}
Manejo de Errores
- Si subagente falla → registrar error, continuar con estrategia
partial - Si timeout → marcar como
timeout, continuar - Si conflicto entre resultados → reportar en
conflictsarray
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.
- 9d ago First seen · 117 lines · 21 tokens per session scan A d07571d8ba2e
quinotospec-swarm-executor 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 836 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 2026-09-03.
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