chore: auto-commit (799 archivos)

- .claude/CLAUDE.md
- .claude/commands/subagentes.md
- .claude/rules/INDEX.md
- .mcp.json
- bash/functions/cybersecurity/analyze_dns.md
- bash/functions/cybersecurity/audit_http_headers.md
- bash/functions/cybersecurity/audit_ssh_config.md
- bash/functions/cybersecurity/check_firewall.md
- bash/functions/cybersecurity/detect_suspicious_users.md
- bash/functions/cybersecurity/encrypt_file.md
- ...

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

python/functions/ml/diffusers_generate.md

@@ -7,7 +7,7 @@ version: "1.0.0"
 purity: impure
 signature: "def diffusers_generate(pipe: Any, cfg: GenerationConfig) -> ImageGenResult"
 description: "Ejecuta inferencia con un pipeline diffusers usando GenerationConfig. Mide duracion y pico de VRAM. Retorna ImageGenResult con imagen PIL, meta y metricas."
-tags: [diffusers, ml, image-generation, inference, vram, metrics]
+tags: [diffusers, ml, image-generation, inference, vram, metrics, pendiente-usar]
 uses_functions: [genconfig_to_diffusers_kwargs_py_ml]
 uses_types: [generation_config_py_ml, image_gen_result_py_ml]
 returns: [image_gen_result_py_ml]

python/functions/ml/diffusers_load_lora.md

@@ -7,7 +7,7 @@ version: "1.0.0"
 purity: impure
 signature: "def diffusers_load_lora(pipe: Any, lora: LoraRef) -> Any"
 description: "Carga un adaptador LoRA en un pipeline diffusers via pipe.load_lora_weights. Si lora.weight != 1.0, aplica set_adapters para escalar la contribucion del LoRA."
-tags: [diffusers, ml, lora, image-generation, fine-tuning]
+tags: [diffusers, ml, lora, image-generation, fine-tuning, pendiente-usar]
 uses_functions: []
 uses_types: [lora_ref_py_ml]
 returns: []

python/functions/ml/diffusers_load_pipeline.md

@@ -7,7 +7,7 @@ version: "1.0.0"
 purity: impure
 signature: "def diffusers_load_pipeline(model: ModelRef, device: str = 'auto', dtype: str = 'fp16') -> Any"
 description: "Carga un pipeline diffusers (AutoPipelineForText2Image) con cache global por (model_key, dtype, device). Segunda llamada con mismos parametros retorna el objeto cacheado sin recargar disco."
-tags: [diffusers, ml, image-generation, pipeline, cache, torch]
+tags: [diffusers, ml, image-generation, pipeline, cache, torch, pendiente-usar]
 uses_functions: [torch_device_select_py_ml]
 uses_types: [model_ref_py_ml]
 returns: []

python/functions/ml/diffusers_set_scheduler.md

@@ -7,7 +7,7 @@ version: "1.0.0"
 purity: impure
 signature: "def diffusers_set_scheduler(pipe: Any, sampler: str) -> Any"
 description: "Reemplaza el scheduler de un pipeline diffusers por la clase correspondiente al sampler solicitado. Usa from_config para heredar configuracion base del modelo."
-tags: [diffusers, ml, scheduler, sampler, image-generation]
+tags: [diffusers, ml, scheduler, sampler, image-generation, pendiente-usar]
 uses_functions: []
 uses_types: []
 returns: []

python/functions/ml/diffusers_unload.md

@@ -7,7 +7,7 @@ version: "1.0.0"
 purity: impure
 signature: "def diffusers_unload(pipe: Any | None = None) -> None"
 description: "Libera la memoria de un pipeline diffusers. Si pipe=None limpia el cache global de diffusers_load_pipeline. Siempre llama gc.collect() y torch.cuda.empty_cache()."
-tags: [diffusers, ml, memory, cleanup, vram, cache]
+tags: [diffusers, ml, memory, cleanup, vram, cache, pendiente-usar]
 uses_functions: []
 uses_types: []
 returns: []

python/functions/ml/genconfig_load_json.md

@@ -7,7 +7,7 @@ version: "1.0.0"
 purity: impure
 signature: "def genconfig_load_json(path: str) -> GenerationConfig"
 description: "Carga y valida un GenerationConfig desde un archivo JSON en disco. Usa pydantic model_validate si disponible; fallback a construccion manual desde dataclass. Raises FileNotFoundError si el archivo no existe."
-tags: [ml, generation, json, io, deserialization]
+tags: [ml, generation, json, io, deserialization, pendiente-usar]
 params:
   - name: path
     desc: "Ruta al archivo JSON generado por genconfig_save_json. Relativa o absoluta."

python/functions/ml/genconfig_to_sdcpp_args.md

@@ -7,7 +7,7 @@ version: "1.0.0"
 purity: pure
 signature: "def genconfig_to_sdcpp_args(cfg: GenerationConfig) -> list[str]"
 description: "Convierte un GenerationConfig a lista de args CLI para stable-diffusion.cpp (sd-cli). Mapea sampler via _SAMPLER_MAP, aplana LoRAs como pares --lora path:weight. Sin I/O ni dependencias externas."
-tags: [ml, sdcpp, stable-diffusion-cpp, cli, converter, pure]
+tags: [ml, sdcpp, stable-diffusion-cpp, cli, converter, pure, pendiente-usar]
 params:
   - name: cfg
     desc: "Instancia de GenerationConfig con los parametros de generacion validados."

python/functions/ml/gpu_info.md

@@ -7,7 +7,7 @@ version: "1.0.0"
 purity: impure
 signature: "def gpu_info() -> list[dict]"
 description: "Consulta nvidia-smi para obtener informacion de cada GPU NVIDIA: nombre, VRAM total y libre, version de driver y CUDA. Devuelve lista vacia si nvidia-smi no esta disponible, sin lanzar excepcion."
-tags: [gpu, nvidia, cuda, vram, hardware, probe, ml, nvidia-smi]
+tags: [gpu, nvidia, cuda, vram, hardware, probe, ml, nvidia-smi, pendiente-usar]
 uses_functions: []
 uses_types: []
 returns: []

python/functions/ml/hf_snapshot_download.md

@@ -7,7 +7,7 @@ version: "1.0.0"
 purity: impure
 signature: "def hf_snapshot_download(repo_id: str, allow_patterns: list[str] | None = None, ignore_patterns: list[str] | None = None, local_dir: str | None = None, token: str | None = None) -> str"
 description: "Descarga un snapshot de un repo HuggingFace Hub (completo o filtrado por patrones glob). Wrapper de huggingface_hub.snapshot_download con ImportError descriptivo. Soporta repos privados/gated via token. Retorna path local del snapshot."
-tags: [huggingface, hf, download, snapshot, model, weights, safetensors, ml, hub]
+tags: [huggingface, hf, download, snapshot, model, weights, safetensors, ml, hub, pendiente-usar]
 uses_functions: []
 uses_types: []
 returns: []

python/functions/ml/image_compare_side_by_side.md

@@ -7,7 +7,7 @@ version: "1.0.0"
 purity: impure
 signature: "def image_compare_side_by_side(a, b, label_a='A', label_b='B', gap_px=16, show_diff=True, show_phash=True) -> dict"
 description: "Compara dos PIL Images lado a lado generando una imagen compuesta A | diff | B con gap configurable. Calcula MSE pixel-wise y perceptual hash (imagehash si disponible). Util para inspeccionar diferencias entre generaciones de imagen."
-tags: [image, compare, diff, phash, mse, pil, pillow, visualization, ml, side-by-side]
+tags: [image, compare, diff, phash, mse, pil, pillow, visualization, ml, side-by-side, pendiente-usar]
 uses_functions: []
 uses_types: []
 returns: []

python/functions/ml/image_grid.md

@@ -7,7 +7,7 @@ version: "1.0.0"
 purity: impure
 signature: "def image_grid(images: list[PIL.Image.Image], cols: int = 4, labels: list[str] | None = None, gap_px: int = 8, bg_color: tuple = (20,20,20)) -> PIL.Image.Image"
 description: "Combina una lista de PIL Images en un grid NxM con gap configurable, fondo oscuro y labels opcionales sobre cada celda. rows se calcula como ceil(n/cols). Retorna una sola PIL.Image RGB."
-tags: [image, grid, pil, pillow, visualization, ml, montage, collage]
+tags: [image, grid, pil, pillow, visualization, ml, montage, collage, pendiente-usar]
 uses_functions: []
 uses_types: []
 returns: []

python/functions/ml/image_save_png.md

@@ -7,7 +7,7 @@ version: "1.0.0"
 purity: impure
 signature: "def image_save_png(img: PIL.Image.Image, path: str, metadata: dict | None = None) -> str"
 description: "Guarda una PIL Image como PNG con metadata embebida en chunks tEXt (prompt, seed, steps, sampler, model). Crea directorio padre si no existe. Retorna path absoluto escrito."
-tags: [image, png, pil, pillow, metadata, save, ml, reproducibility]
+tags: [image, png, pil, pillow, metadata, save, ml, reproducibility, pendiente-usar]
 uses_functions: []
 uses_types: []
 returns: []

python/functions/ml/safetensors_inspect.md

@@ -7,7 +7,7 @@ version: "1.0.0"
 purity: impure
 signature: "def safetensors_inspect(path: str) -> dict"
 description: "Lee SOLO el header de un archivo .safetensors sin cargar los tensores en RAM. Retorna metadata del modelo, lista de tensores con dtype/shape/offsets, tamano total y conteo. Util para inspeccionar checkpoints de varios GB sin agotarlos en memoria."
-tags: [safetensors, model, inspect, header, ml, huggingface, checkpoint, dtype, shape]
+tags: [safetensors, model, inspect, header, ml, huggingface, checkpoint, dtype, shape, pendiente-usar]
 uses_functions: []
 uses_types: []
 returns: []

python/functions/ml/sdcpp_python_generate.md

@@ -7,7 +7,7 @@ version: "1.0.0"
 purity: impure
 signature: "def sdcpp_python_generate(sd: Any, cfg: GenerationConfig) -> ImageGenResult"
 description: "Genera una imagen con un StableDiffusion (stable-diffusion-cpp-python) usando GenerationConfig como contrato. Mapea sampler, mide duracion y retorna ImageGenResult con meta del backend."
-tags: [ml, stable-diffusion, sdcpp, inference, backend, generate, txt2img]
+tags: [ml, stable-diffusion, sdcpp, inference, backend, generate, txt2img, pendiente-usar]
 uses_functions: [sdcpp_python_load_py_ml]
 uses_types: [generation_config_py_ml, image_gen_result_py_ml]
 returns: [image_gen_result_py_ml]

python/functions/ml/vram_budget.md

@@ -7,7 +7,7 @@ version: "1.0.0"
 purity: pure
 signature: "def vram_budget(gpu_vram_total_mb: int, model_type: str, quantization: str, n_loras: int = 0, width: int = 1024, height: int = 1024, batch_size: int = 1) -> dict"
 description: "Estima la VRAM requerida para ejecutar un modelo de generacion de imagen via heuristicas tabuladas por (model_type, quantization). Retorna VRAM estimada, si cabe en la GPU indicada, headroom disponible, y warnings por incompatibilidades (lora+quant) o falta de VRAM. Funcion pura: solo lookup y aritmetica, sin GPU ni runtime."
-tags: [ml, vram, gpu, budget, stable-diffusion, flux, sdxl, quantization, lora, estimation, pure]
+tags: [ml, vram, gpu, budget, stable-diffusion, flux, sdxl, quantization, lora, estimation, pure, pendiente-usar]
 uses_functions: []
 uses_types: []
 returns: []