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 danielgap/openclaw-planitor --skill data-extractiongit clone --depth 1 https://github.com/danielgap/openclaw-planitorWrote 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/danielgap/openclaw-planitor/data-extraction)<a href="https://agentmods.dev/skills/danielgap/openclaw-planitor/data-extraction"><img src="https://agentmods.dev/badge/skills/danielgap/openclaw-planitor/data-extraction/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/danielgap/openclaw-planitor/data-extraction"><img src="https://agentmods.dev/badge/skills/danielgap/openclaw-planitor/data-extraction.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 | $0.00000 | $0.00701 |
| Opus 5.5 | $0.00000 | $0.00280 |
| Sonnet 5.5 | $0.00000 | $0.00140 |
| Haiku 4.5 | $0.00000 | $0.00070 |
Grade A, and why
data-extraction scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **Webs**: Usar `curl -sL "https://r.jina.ai/URL"` para texto limpio How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Extraction Skill
Propósito
Extraer, estructurar y validar datos de múltiples fuentes para alimentar el pipeline de plan de negocio.
Capacidades
1. Extracción de Datos Estructurados
- Parsear JSON, CSV, XML de cualquier fuente
- Extraer tablas de HTML/markdown
- Convertir texto libre a datos tabulados
- Normalizar formatos (monedas, fechas, unidades)
2. Extracción de Documentos
- PDFs: Usar
lit parse archivo.pdf --ocr-language spao Jina Reader - Webs: Usar
curl -sL "https://r.jina.ai/URL"para texto limpio - Imágenes: Extraer texto con OCR cuando sea necesario
- Excel/CSV: Leer directamente con herramientas disponibles
3. Validación Cruzada
Para cada dato crítico del plan:
- Buscar en al menos 2 fuentes independientes
- Comparar valores
- Si coinciden → ✅ Confirmado
- Si discrepan → ⚠️ Flag con ambas fuentes
- Si solo hay 1 fuente → ❓ No confirmado (usar como referencia)
4. Categorías de Datos
| Categoría | Ejemplos | Fuentes típicas |
|---|---|---|
| Demográficos | Población, renta, turismo | INE, ayuntamientos |
| Mercado | TAM/SAM/SOM, crecimiento | Informes sectoriales, cámaras |
| Competencia | Players, cuota, precios | Webs, registros, Google Maps |
| Costes | Alquiler, salarios, suministros | Portales inmobiliarios, convenios |
| Regulación | Licencias, CNAE, impuestos | BOE, ayuntamientos, AEAT |
| Financieros | Tipos de interés, inflación | BCE, INE, Banco de España |
5. Normalización de Datos
Reglas:
- Moneda: siempre EUR (€) salvo que se especifique otra
- Porcentajes: formato decimal (0.15 = 15%)
- Fechas: ISO 8601 (YYYY-MM-DD)
- Cantidades: sin separadores de miles, punto decimal
- Fuentes: SIEMPRE documentadas
6. Detección de Datos Obsoletos
| Antigüedad | Acción |
|---|---|
| < 6 meses | ✅ Usar directamente |
| 6-12 meses | ⚠️ Usar con advertencia |
| 1-2 años | ⚠️ Usar solo como referencia, buscar más reciente |
| > 2 años | ❌ No usar, buscar alternativa |
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 · 72 lines · 0 tokens per session scan A 8e2fa2818467
data-extraction is a skill published in the GitHub repository danielgap/openclaw-planitor (5 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 701 tokens. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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