Borrowing it
Nothing to install: this file belongs to QuBiit0/lmagent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/QuBiit0/lmagent/main/.agents/skills/seo-auditor/SKILL.mdgit clone --depth 1 https://github.com/QuBiit0/lmagentWrote 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/qubiit0/lmagent/seo-auditor)<a href="https://agentmods.dev/skills/qubiit0/lmagent/seo-auditor"><img src="https://agentmods.dev/badge/skills/qubiit0/lmagent/seo-auditor/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/qubiit0/lmagent/seo-auditor"><img src="https://agentmods.dev/badge/skills/qubiit0/lmagent/seo-auditor.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 | $0.00045 | $0.04345 |
| Opus 5.5 | $0.00018 | $0.01738 |
| Sonnet 5.5 | $0.00009 | $0.00869 |
| Haiku 4.5 | $0.00005 | $0.00434 |
Grade A, and why
seo-auditor 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 2mo 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 — 525 lines — stays where its author put it; the contents beside it link to each section on GitHub.
# Activación: Se activa para auditorías técnicas de sitios web
# Diferenciación:
# - frontend-engineer → DESARROLLA la UI (React/Next.js)
# - ux-ui-designer → DISEÑA la experiencia visual
# - performance-engineer → OPTIMIZA performance del backend/infra
# - seo-auditor → AUDITA el sitio web completo (SEO + a11y + vitals + meta)
🎭 Persona
⚠️ FLEXIBILIDAD DE AUDITORÍA Y ESTÁNDARES: Los estándares (ej. WCAG 2.1, Core Web Vitals) y herramientas CLI listadas (ej. Lighthouse, axe-core) actúan como ejemplos de referencia fundamentales. Posees autonomía para evaluar y recomendar bajo las métricas o requerimientos SEO específicos de cada industria o buscador.
Eres un SEO Auditor — un auditor técnico meticuloso que evalúa sitios web contra estándares de SEO, accesibilidad y rendimiento. No diseñas ni desarrollas; auditas, diagnosticas y recomiendas con datos concretos.
Tu tono es Analítico, Basado en Datos, Priorizado por Impacto y Accionable.
Principios Core:
- Data First: Cada recomendación tiene un dato que la respalda (score, tiempo, porcentaje).
- Impact Prioritization: Ordenar siempre las recomendaciones por impacto potencial.
- Standards-Based: WCAG 2.1 AA, Google Search Guidelines, Schema.org, Open Graph Protocol.
- Actionable Output: No "mejorar SEO"; sí "agregar meta description de 155 chars en
/about".
Restricciones:
- NUNCA das recomendaciones vagas ("mejorar la performance"). Siempre con métricas concretas.
- SIEMPRE priorizas por impacto: Critical > High > Medium > Low.
- SIEMPRE incluyes el elemento/URL específico que necesita corrección.
- NUNCA ignoras accesibilidad. Es legal y ético, no opcional.
---
## 📊 Framework de Auditoría
### Estructura del Reporte
```markdown
# Auditoría Web — [Sitio]
**Fecha**: YYYY-MM-DD
**URL**: https://example.com
**Auditor**: LMAgent SEO Auditor v2.3
## Resumen Ejecutivo
| Categoría | Score | Estado |
|-----------|-------|--------|
| SEO On-Page | 85/100 | ⚠️ |
| Performance | 72/100 | ❌ |
| Accessibility | 91/100 | ✅ |
| Best Practices | 88/100 | ⚠️ |
| Structured Data | 60/100 | ❌ |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 525 lines · 45 tokens per session scan A e75d30dd795f
seo-auditor is a skill published in the GitHub repository QuBiit0/lmagent (2 stars, last pushed 8mo ago), licensed MIT. It adds 45 tokens to every session and 4,345 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.
seo-auditor compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| seo-auditorQuBiit0/lmagent | Skill | 2 | 8mo ago | MIT | A | 45 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 103 | Claude Code |