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 betobetico/claude-para-abogados --skill revision-tabulargit clone --depth 1 https://github.com/betobetico/claude-para-abogadosWrote 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/betobetico/claude-para-abogados/revision-tabular)<a href="https://agentmods.dev/skills/betobetico/claude-para-abogados/revision-tabular"><img src="https://agentmods.dev/badge/skills/betobetico/claude-para-abogados/revision-tabular/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/betobetico/claude-para-abogados/revision-tabular"><img src="https://agentmods.dev/badge/skills/betobetico/claude-para-abogados/revision-tabular.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 | $0.00024 | $0.00965 |
| Opus 5.5 | $0.00010 | $0.00386 |
| Sonnet 5.5 | $0.00005 | $0.00193 |
| Haiku 4.5 | $0.00002 | $0.00097 |
Grade A, and why
revision-tabular-dd 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 15d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Propósito
Esta skill procesa los documentos de un data room virtual (VDR) para generar una tabla de revisión de due diligence. Cada documento se convierte en una fila con categorización, hallazgos clave, nivel de riesgo y referencia normativa. Diseñada para la fase de revisión documental de operaciones de M&A, inversión o financiación.
Instrucciones
Paso 1 — Indexar documentos
- Leer la lista de documentos proporcionados por el usuario.
- Clasificar cada documento en una categoría:
- Societario (escrituras, estatutos, actas, poderes)
- Contratos (mercantiles, laborales, financieros)
- Laboral (plantilla, convenios, litigios laborales)
- Fiscal (declaraciones, actas inspección, certificados)
- Regulatorio (licencias, autorizaciones, permisos)
- Litigios (demandas, sentencias, arbitrajes)
- Propiedad intelectual (registros, licencias, cesiones)
- Inmobiliario (títulos, arrendamientos, cargas)
Paso 2 — Analizar cada documento
Para cada documento:
- Identificar tipo y fecha del documento.
- Extraer hallazgos clave (hechos relevantes, cifras, obligaciones).
- Evaluar nivel de riesgo: ALTO / MEDIO / BAJO / INFORMATIVO.
- Citar la norma aplicable (artículo concreto).
- Anotar si falta algún documento relacionado.
Paso 3 — Detectar ausencias
- Documentos esperados según el índice del VDR que no están.
- Documentos obligatorios por ley que no aparecen (ej. cuentas anuales, libros de actas).
- Versiones desactualizadas de documentos que deberían estar vigentes.
Paso 4 — Generar tabla
Formato de salida
## Revisión tabular de due diligence
**Operación:** [nombre]
**Fecha de revisión:** [fecha]
**Documentos analizados:** [número]
**Documentos pendientes:** [número]
### Tabla de revisión
| # | Documento | Categoría | Fecha | Hallazgos clave | Riesgo | Referencia normativa | Notas |
|---|-----------|-----------|-------|------------------|--------|----------------------|-------|
| 1 | [nombre] | [cat] | [fecha] | [hallazgo] | [nivel] | [norma art. X] | [nota] |
### Resumen por categoría
| Categoría | Docs revisados | Riesgo alto | Riesgo medio | Pendientes |
|-----------|----------------|-------------|--------------|------------|
| [cat] | [n] | [n] | [n] | [n] |
### Documentos ausentes
| Documento esperado | Categoría | Obligatoriedad | Impacto |
|--------------------|-----------|----------------|---------|
| [nombre] | [cat] | Legal/Recomendado | [detalle] |
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.
- 15d ago First seen · 90 lines · 24 tokens per session scan A 0987af638a3f
revision-tabular-dd is a skill published in the GitHub repository betobetico/claude-para-abogados (43 stars, last pushed 16d ago), licensed Apache-2.0. It adds 24 tokens to every session and 965 once invoked, about $0.0001 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 2026-10-01.
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