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.
git clone --depth 1 https://github.com/gonzalezpazmonica/saviaWrote 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/commands/gonzalezpazmonica/savia/banking-data-governance)<a href="https://agentmods.dev/commands/gonzalezpazmonica/savia/banking-data-governance"><img src="https://agentmods.dev/badge/commands/gonzalezpazmonica/savia/banking-data-governance/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/commands/gonzalezpazmonica/savia/banking-data-governance"><img src="https://agentmods.dev/badge/commands/gonzalezpazmonica/savia/banking-data-governance.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 | $0.00966 |
| Opus 5 | $0.00012 | $0.00483 |
| Sonnet 5 | $0.00005 | $0.00193 |
| Haiku 4.5 | $0.00002 | $0.00097 |
Grade A, and why
banking-data-governance 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 6d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- banking-data-governance — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/banking-data-governance [--project {nombre}] [--focus lineage|classification|features|gdpr]
🏦 Audita el gobierno de datos de tu proyecto bancario: lineage, clasificación, GDPR.
Cargar perfil y skill
Grupo: Architecture & Tech — cargar identity.md + projects.md + preferences.md.
Reference: @.opencode/skills/banking-architecture/references/data-governance-banking.md
Parámetros
--project {nombre}— Proyecto (default: activo)--focus {area}— Focalizar:lineage|classification|features|gdpr(default: all)
Flujo
Paso 1 — Detectar stack de datos
Escanear config, deps y código para identificar:
- Data warehouse: Snowflake, BigQuery, Redshift, Synapse
- Data lake: S3, ADLS, GCS con Iceberg/Delta/Hudi
- ETL/ELT: Airflow, dbt, Informatica, Spark
- Feature store: Feast, Tecton, SageMaker FS
- Catálogo: Collibra, Alation, DataHub, Apache Atlas
- Virtualización: Denodo
Paso 2 — Auditar Data Classification
Escanear modelos de datos, schemas y código buscando:
| Campo | Clasificación esperada | Check |
|---|---|---|
| PAN, CVV, PIN | PCI — tokenizado | ❌ si plain text |
| Nombre, DNI, email | PII — cifrado | ❌ si sin cifrar |
| Saldo, scoring | Confidential — acceso restringido | ⚠️ si en logs |
| IBAN | Semi-public — maskeado | ⚠️ si completo en logs |
Verificar que existe data-classification.md o equivalente documentado.
Paso 3 — Auditar Data Lineage
Evaluar trazabilidad:
- ¿Existe documentación de lineage (manual o automática)?
- ¿Hay herramientas de lineage integradas (Atlas, Collibra, DataHub)?
- ¿Los pipelines tienen metadata de origen y transformación?
- ¿Se puede trazar un dato regulatorio desde fuente hasta reporte?
Score de madurez: L0 (sin lineage) → L4 (automático + alertas).
Paso 4 — Auditar Feature Store (si aplica)
- ¿Existe feature store (batch + real-time)?
- ¿Features versionadas y con lineage?
- ¿Point-in-time correctness para training vs serving?
- ¿Feature drift monitoreado?
- ¿Documentación de cada feature (owner, source, freshness)?
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.
- 6d ago First seen · 113 lines · 24 tokens per session scan A 23a860f6c37e
banking-data-governance is a command published in the GitHub repository gonzalezpazmonica/savia (50 stars, last pushed yesterday), licensed MIT. It adds 24 tokens to every session and 966 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 2026-09-06.
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