Generalize catalog/rule descriptions and add Intended Use & Legal Compliance section

README.md

@@ -11,26 +11,34 @@ tags:
   - multi-task-learning
   - onnx
   - int8
-  - prowlarr
-  - sonarr
-  - radarr
 pipeline_tag: text-classification
 ---
 
 <h1 align="center">Armiger</h1>
 
 <p align="center">
-  <strong>Fast 8.3 MB universal CPU torrent &amp; media classifier for Bitmagnet, Prowlarr, Sonarr, and Radarr.</strong><br>
+  <strong>Fast 8.3 MB universal CPU torrent &amp; media classifier for Bitmagnet and self-hosted media libraries.</strong><br>
   Predicts 8 calibrated decision heads simultaneously in 0.42 ms batched (2.44 ms single-item) on any CPU — matching or outperforming Frontier Cloud LLMs at ~900x faster speed and $0 API cost.
 </p>
 
+## Intended Use & Legal Compliance
+
+`Armiger`, `Armiger Ultra`, and all bundled plugins are open-source machine learning and cryptographic metadata-classification utilities designed strictly for **lawful use cases**, including:
+- Organizing and indexing licensed, public-domain, Creative Commons, and open-source digital media, software distributions (e.g., Linux ISOs, open-source games), and educational archives (e.g., OpenCourseWare, LibriVox, Project Gutenberg).
+- Automated cybersecurity screening, fake-seeder honeypot detection, and disguised executable/malware filtering (`.mkv.exe`, `.scr`, `.vbs`) in peer-to-peer and decentralized storage research.
+- Child safety (CSAM/CSAE) pre-ingest blocking, cryptographic tombstone revocation, and adult/NSFW namespace isolation for self-hosted and decentralized indexers.
+
+**NorviTech does not condone, encourage, or support copyright infringement or the unauthorized distribution of copyrighted works.** Users are solely responsible for ensuring that their use of these models and plugins complies with all applicable local, national, and international copyright and data-protection laws.
+
+---
+
 <p align="center">
   <a href="https://norvitech.com"><img alt="NorviTech Suite" src="https://img.shields.io/badge/NorviTech-Suite-FD8024.svg"></a>
   <a href="https://huggingface.co/NorviTech/armiger-ultra"><img alt="Armiger Ultra" src="https://img.shields.io/badge/Armiger_Ultra-GPU_%2B_Swarm_Suite-10B981.svg"></a>
   <img alt="Licence Apache-2.0" src="https://img.shields.io/badge/licence-Apache--2.0-blue.svg">
 </p>
 
-**Armiger** (`NorviTech/armiger`) is an ultra-compact (`8.3 MB`), zero-tokenizer byte-level RoPE Transformer + File-Tree Encoder designed for real-time BitTorrent, DHT, Usenet, and media automation (`Bitmagnet`, `Prowlarr`, `Sonarr`, `Radarr`) classification on any CPU.
+**Armiger** (`NorviTech/armiger`) is an ultra-compact (`8.3 MB`), zero-tokenizer byte-level RoPE Transformer + File-Tree Encoder designed for real-time BitTorrent, DHT, Usenet, and media automation (`Bitmagnet` and self-hosted media libraries) classification on any CPU.
 
 Unlike rule parsers (`GuessIt`, `PTT`, `RTN`, `PTN`, `Anitomy`) that only recognize video filenames or `360M+` parameter subword models (`MIMMO BERT`) that require `~1.4 GB` of weights, **Armiger** reads raw UTF-8 title bytes and internal file trees directly to predict **8 calibrated classification heads** in a single forward pass.
 
@@ -60,10 +68,10 @@ Unlike rule parsers (`GuessIt`, `PTT`, `RTN`, `PTN`, `Anitomy`) that only recogn
 | :--- | :---: | :---: | :--- |
 | **[`NorviTech/armiger-swarm-survival`](https://huggingface.co/NorviTech/armiger-swarm-survival)** | **Yes** (`swarm_adapter.pt`, `swarm_survival.py`) | `163 KB` | **SwarmSurvivalNet v2 & Honeypot Residual Adapter:** **`96.83%`** Swarm Liveliness AUROC (vs. `53.04%` raw seeders), **`100.0%`** fake-seeder malware trap recall, **`0%`** content-category flip guarantee. |
 | **[`NorviTech/armiger-swarm-priors`](https://huggingface.co/NorviTech/armiger-swarm-priors)** | **Yes** (`swarm_priors.py`) | `29.4 KB` | **Empirical Bayes Swarm & Release-Group Priors:** 4-pathway tracker scrape prior engine, mandatory modality dropout (`p=0.60`), anomaly feature extraction, and public-tracker passkey safety filter. |
-| **[`NorviTech/armiger-zero-cue-catalog`](https://huggingface.co/NorviTech/armiger-zero-cue-catalog)** | **Yes** (`zero_cue_plugin.py`, `validated_zero_cue_catalog.json`) | `36.0 MB` | **Zero-Cue Catalog & Structural Disambiguator:** Offline 929,400-key normalized `TMDB`/`TVDB`/`AniDB`/`Manami` lookup + structural pack/ROM/VN/course rules; lifts Movie-vs-TV accuracy to **`99.46%`** and 11-class accuracy to **`98.48%`** (`98.93%` Hard Edge-Cases). |
+| **[`NorviTech/armiger-zero-cue-catalog`](https://huggingface.co/NorviTech/armiger-zero-cue-catalog)** | **Yes** (`zero_cue_plugin.py`, `validated_zero_cue_catalog.json`) | `36.0 MB` | **Zero-Cue Catalog & Structural Disambiguator:** Offline 929,400-key normalized title-year & entity reference lookup + structural multi-file & format disambiguation rules; lifts Movie-vs-TV accuracy to **`99.46%`** and 11-class accuracy to **`98.48%`** (`98.93%` Hard Edge-Cases). |
 | **[`NorviTech/armiger-audio-guard`](https://huggingface.co/NorviTech/armiger-audio-guard)** | **Yes** (`audio_language_guard.py`) | `4.2 KB` | **Cross-Head Audio Language & Anime Dub Guard:** Couples `title_language` (`P(Foreign Title)`) with `lang` head to disambiguate `.en.` prepositions, `<Foreign>.ENG.Sub`, regional dubs, and `MULTi (FR EN)` tags; reaches **`98.72%`** Gold Standard and **`99.88%`** Hard Edge-Case audio accuracy. |
-| **[`NorviTech/armiger-calibration-dht`](https://huggingface.co/NorviTech/armiger-calibration-dht)** | **Yes** (`calibration.json`, `calibration_and_dht.py`, `armiger_dht_rsi.py`) | `115 KB` | **Conformal Calibration, BEP-44 DHT Updater & Distributed RSI Engine:** Per-head temperature scaling ($T_h$), Mondrian safety gates (`99.95%` junk balanced accuracy), `Ed25519` threshold-signed `BEP-44`/`BEP-46` DHT hot-reload, universal `*Arr`/qBittorrent/Transmission/ffprobe ground-truth RSI, `X25519`+`ChaCha20-Poly1305` AEAD, distinct-ASN quorum, and 500-canary regression gate (`36/36` tests). |
-| **[`NorviTech/armiger-dht-db-sync`](https://huggingface.co/NorviTech/armiger-dht-db-sync)** | **Yes** (`csam_guard.py`, `armiger_dht_db_sync.py`) | `98 KB` | **Modular, CSAM-Protected, Encrypted BEP-44/BEP-46 DHT Database Sync:** Multi-stage CSAM & abuse pre-ingest blocker, `Ed25519`-signed blinded `SHA-256` tombstone purge engine, 10-category $	imes$ 14-language $	imes$ 7-quality sharded subscriptions with strict default-off `xxx` isolation, `X25519`+`ChaCha20-Poly1305` AEAD, binary Merkle proofs, and $K$-of-$N$ distinct-ASN Sybil quorum (`27/27` tests). |
+| **[`NorviTech/armiger-calibration-dht`](https://huggingface.co/NorviTech/armiger-calibration-dht)** | **Yes** (`calibration.json`, `calibration_and_dht.py`, `armiger_dht_rsi.py`) | `115 KB` | **Conformal Calibration, BEP-44 DHT Updater & Distributed RSI Engine:** Per-head temperature scaling ($T_h$), Mondrian safety gates (`99.95%` junk balanced accuracy), `Ed25519` threshold-signed `BEP-44`/`BEP-46` DHT hot-reload, universal media-webhook/qBittorrent/Transmission/ffprobe ground-truth RSI, `X25519`+`ChaCha20-Poly1305` AEAD, distinct-ASN quorum, and 500-canary regression gate (`36/36` tests). |
+| **[`NorviTech/armiger-dht-db-sync`](https://huggingface.co/NorviTech/armiger-dht-db-sync)** | **Yes** (`csam_guard.py`, `armiger_dht_db_sync.py`) | `98 KB` | **Modular, CSAM-Protected, Encrypted BEP-44/BEP-46 DHT Database Sync:** Multi-stage CSAM & abuse pre-ingest blocker, `Ed25519`-signed blinded `SHA-256` tombstone purge engine, 10-category $\times$ 14-language $\times$ 7-quality sharded subscriptions with strict default-off `xxx` isolation, `X25519`+`ChaCha20-Poly1305` AEAD, binary Merkle proofs, and $K$-of-$N$ distinct-ASN Sybil quorum (`27/27` tests). |
 
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