chore: auto-commit (286 archivos)

- .claude/agents/fn-orquestador/SKILL.md
- .claude/commands/fn_claude.md
- .claude/rules/INDEX.md
- .claude/rules/cpp_apps.md
- .claude/rules/ids_naming.md
- CHANGELOG.md
- apps/dag_engine/README.md
- apps/dag_engine/api.go
- apps/dag_engine/dags_migrated/example.yaml
- apps/dag_engine/dags_migrated/example_lineage_tracking.yaml
- ...

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

dev/flows/0002-aemet-madrid.md

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+---
+name: aemet-madrid
+id: 0002
+status: pending
+created: 2026-05-16
+updated: 2026-05-16
+priority: medium
+risk: low
+related_issues: [0097]
+apps:
+  - dag_engine
+  - data_factory
+  - footprint_geo_stack
+trigger: cron
+schedule: "0 * * * *"
+expected_runtime_s: 10
+tags: [api, weather, geo, http-only]
+---
+
+## Goal
+
+Probar path HTTP-only (sin Chrome/CDP). Extractor REST -> data_factory -> sink geo (PostGIS via footprint_geo_stack). Demuestra que el stack tambien sirve para APIs publicas + datos georeferenciados.
+
+## Pre-requisitos
+
+- API key AEMET (gratis, signup). Guardar en `pass insert aemet/api-key`.
+- `footprint_geo_stack` corriendo (PostGIS :5432 + Martin tiles :3000).
+- dag_engine activo.
+
+## Flow
+
+1. Crear funcion del registry `aemet_get_weather_py_infra` (o usar `http_get_json_py_infra` directamente si la API responde JSON simple).
+2. Endpoint AEMET observacion convencional: `GET https://opendata.aemet.es/opendata/api/observacion/convencional/datos/estacion/<id>` con header `api_key`.
+3. Schema esperado: `[{ts, temp, humidity, pressure, wind_speed, lat, lon}, ...]`.
+4. Sink: INSERT en PostGIS tabla `weather_madrid (ts, temp, humidity, pressure, geom geometry(Point, 4326))`.
+5. Crear node en data_factory: `{kind: 'database', label: 'postgis_weather'}` (sink declarado).
+6. DAG `aemet_madrid_hourly.yaml`:
+   ```yaml
+   name: aemet-madrid
+   schedule: "0 * * * *"
+   steps:
+     - name: extract
+       function: aemet_get_weather_py_infra
+       args: ["--station", "3195", "--out", "/tmp/aemet.json"]
+     - name: load_postgis
+       function: db_insert_row_go_infra
+       args: ["--db", "postgres://...", "--table", "weather_madrid", "--from-json", "/tmp/aemet.json"]
+       depends: [extract]
+   ```
+7. Verificar Martin tiles renderiza overlay (opcional).
+
+## Acceptance
+
+- [ ] Funcion AEMET extractor existe (creada o reusada `http_get_json_*`).
+- [ ] DAG corre 2x consecutivas via scheduler.
+- [ ] PostGIS tabla `weather_madrid` tiene >=2 filas.
+- [ ] data_factory muestra node `aemet_madrid` kind=extractor + node `postgis_weather` kind=database con `last_seen_at` reciente.
+- [ ] Martin tile server sirve overlay weather (opcional).
+
+## Telemetria esperada
+
+- `function_stats.http_get_json_py_infra` o `aemet_get_weather_py_infra`: calls_24h += 24 (1/hora).
+- `data_factory.runs`: 24 entries/dia.
+- `data_factory.databases.last_seen_at` actualizado por sink.
+
+## Notas
+
+- Sin LLM/CDP. Mas barato que flow 0001.
+- Caso minimal para servicios geo. Si funciona, sirve de plantilla para mas extractores API.