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 kokesaurio/mercadolibre-algoritmodigital --skill competencia-mlgit clone --depth 1 https://github.com/kokesaurio/mercadolibre-algoritmodigitalWrote 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/kokesaurio/mercadolibre-algoritmodigital/competencia-ml)<a href="https://agentmods.dev/skills/kokesaurio/mercadolibre-algoritmodigital/competencia-ml"><img src="https://agentmods.dev/badge/skills/kokesaurio/mercadolibre-algoritmodigital/competencia-ml/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/kokesaurio/mercadolibre-algoritmodigital/competencia-ml"><img src="https://agentmods.dev/badge/skills/kokesaurio/mercadolibre-algoritmodigital/competencia-ml.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00087 | $0.00655 |
| Opus 5 | $0.00044 | $0.00328 |
| Sonnet 5 | $0.00017 | $0.00131 |
| Haiku 4.5 | $0.00009 | $0.00065 |
Grade A, and why
competencia-ml 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 2d 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.
What it actually says
Análisis de competencia en MercadoLibre
Radiografía de posición competitiva con datos, terminando en decisiones de precio concretas, no en observaciones genéricas.
Requisito
Herramientas ml_* del conector de Algoritmo Digital. Si no están, indicá
agregar el conector desde https://mcp.algoritmodigital.com.ar y frená.
Flujo
ml_competitividad— posición de precio de cada publicación frente a su competencia directa. Es el corazón del análisis.ml_competidores— los vendedores monitoreados: reputación, ventas estimadas, precio promedio. Si el usuario quiere seguir a uno nuevo, indicá que se agrega desde el panel del CRM.ml_cambios_precio— quién movió precios últimamente y hacia dónde; detecta guerras de precio antes de que duelan.ml_catalogo— en qué publicaciones de catálogo se está ganando o perdiendo la buy box y por cuánto.ml_mercado— tendencia general de la categoría si el usuario pregunta por el mercado y no solo por sus ítems.
Formato del análisis
🥊 Posición competitiva — [tienda]
- Semáforo general: en cuántas publicaciones se está caro / competitivo / barato.
- Los 3-5 casos que importan: ítems donde se pierde catálogo o ventas por precio, con el número exacto (nuestro precio vs el del competidor, y la diferencia).
- Movimientos recientes de competidores que cambian el juego.
- Recomendación por ítem: subir, bajar, sostener — siempre validada
contra
ml_rentabilidadoml_simular_precios: nunca recomendar un precio que dé margen negativo, y decirlo explícitamente cuando igualar a la competencia no cierra con los costos.
Aplicar cambios de precio
Si el usuario decide cambiar precios, usá ml_actualizar_publicacion de a
un ítem, mostrando antes → después y esperando confirmación explícita de
cada cambio. Después verificá con ml_publicaciones.
Qué no hacer
- No recomendar "bajar para competir" sin mirar el margen: ese consejo gratis es el que funde vendedores.
- No presentar estimaciones de ventas de competidores como datos exactos: son estimaciones y hay que decirlo.
- No cambiar ningún precio sin confirmación explícita por ítem.
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.
- 2d ago First seen · 55 lines · 87 tokens per session scan A 0ff7490d4f1f
competencia-ml is a skill published in the GitHub repository kokesaurio/mercadolibre-algoritmodigital (0 stars, last pushed 3d ago), licensed MIT. It adds 87 tokens to every session and 655 once invoked, about $0.0004 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 2026-09-09.
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