Skip to content
Back to skills

Deployment And Data Ops

ASecurity

"Operate Jarbas and Rosie service setup, data loading, validation,

  • 247 stars
  • 0 votes
  • 0 copies
  • 3 views
  • Added September 9, 2026
databasespythongosqlnodedjangodockergitapifrontend

Works with

  • api

Security analysis

A100/100

Pro scans all 9 files and shows the line behind each finding

Scanned September 9, 2026

npx -y skills add VectorSpaceLab/AREX-Skill --skill deployment-and-data-ops --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Deployment And Data Ops?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Deployment And Data Ops
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/vectorspacelab-deployment-and-data-ops/badge)](https://www.skillsdirectory.com/skills/vectorspacelab-deployment-and-data-ops)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: deployment-and-data-ops
description: "Operate Jarbas and Rosie service setup, data loading, validation,
  assets, and maintenance workflows safely."
disable-model-invocation: true
metadata:
  disco-role: operating
license: MIT
---

# Deployment and Data Operations

Use this sub-skill when the task is to install, start, seed, validate, or troubleshoot the service/data lifecycle around Serenata de Amor's Jarbas Django service and Rosie outputs.

Route elsewhere:

- Jarbas REST endpoint semantics, serializers, filters, and response shapes are owned by `jarbas-data-api`.
- Rosie classifier behavior, model/cache details, and `suspicions.xz` generation are owned by `rosie-suspicion-pipeline`.
- Production deployment automation, DigitalOcean updates, cron jobs, and external API publishing are reference-only here; do not execute credential-bound automation unless a human explicitly authorizes the exact target environment.

## Fast operating map

1. Identify the environment path: Docker Compose local, local Python service stack, or reference-only production maintenance.
2. Prepare configuration using [configuration.md](references/configuration.md). Never invent or print real credentials.
3. Bring up prerequisites from [docker-and-services.md](references/docker-and-services.md): legacy Python dependencies, PostgreSQL for full Jarbas semantics, optional RabbitMQ/Celery, cache, and optional Node/Elm asset tooling.
4. Run the safe preflight helper before service-changing operations:

   ```console
   $ python sub-skills/deployment-and-data-ops/scripts/jarbas_manage_check.py --repo-root <serenata-checkout>
   ```

   Use `--no-run` to inspect the command and default environment keys without invoking Django.
5. Seed data using [data-loading.md](references/data-loading.md) and [management-commands.md](references/management-commands.md). The safe sample order is migrations first, then reimbursements, companies, suspicions, search vector, and optional tweets/social-media/receipt commands.
6. Build or collect frontend/static assets only when the legacy Node/Elm stack is available; see [frontend-assets.md](references/frontend-assets.md).
7. For maintenance scripts and one-off research data acquisition, classify the script before running anything using [research-and-maintenance-scripts.md](references/research-and-maintenance-scripts.md).
8. Diagnose known failures with [troubleshooting.md](references/troubleshooting.md).

## Safe defaults and validation boundaries

- `manage.py check` is a configuration/import preflight; it does not replace migrations, sample data loads, API tests, or PostgreSQL-backed search validation.
- SQLite can be useful for `manage.py check`, but full Jarbas behavior uses PostgreSQL-specific fields and search vectors.
- `tweets`, `tweet`, `receipts`, `receipts_text`, `socialmedia`, and `update` have side effects or external dependencies; read their command notes before use.
- Do not run DigitalOcean, cron, deploy, or research fetch scripts as generic setup. Treat them as historical/maintainer workflows unless the user provides credentials, target environment, rollback plan, and authorization.

## Bundled files

- [configuration.md](references/configuration.md) — environment variables, secret handling, and check-time defaults.
- [docker-and-services.md](references/docker-and-services.md) — Docker Compose topology, local install prerequisites, startup/validation sequences.
- [data-loading.md](references/data-loading.md) — sample dataset formats, load order, validation counts, receipt text and social-media CSV assumptions.
- [management-commands.md](references/management-commands.md) — command table, flags, prerequisites, outputs, and safety classification.
- [frontend-assets.md](references/frontend-assets.md) — Node 8 / Elm 0.18 asset workflow and pitfalls.
- [research-and-maintenance-scripts.md](references/research-and-maintenance-scripts.md) — research, cron, update, and deploy script classifications.
- [troubleshooting.md](references/troubleshooting.md) — common failures and recovery steps.
- [jarbas_manage_check.py](scripts/jarbas_manage_check.py) — safe wrapper around `python manage.py check`.

Files in this skill

  • SKILL.md4.1 KB
  • references/configuration.md5.1 KB
  • references/data-loading.md8.7 KB
  • references/docker-and-services.md7.1 KB
  • references/frontend-assets.md3.9 KB
  • references/management-commands.md8.8 KB
  • references/research-and-maintenance-scripts.md6.2 KB
  • references/troubleshooting.md7.9 KB
  • scripts/jarbas_manage_check.py6.3 KB

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.