| --- |
| license: mit |
| tags: |
| - embeddings |
| - skill-retrieval |
| - claude-code |
| --- |
| |
| # superskillret prebuilt index — full-context |
|
|
| Prebuilt embedding index for the [superskillret](https://github.com/ThakiCloud/SUPERSKILLRET) Claude Code plugin. |
|
|
| Unlike the v1 index (which embedded only `name + description`), v2 encodes |
| the **full skill body** (`name + description + body`) up to |
| `max_seq_length=32768` tokens. Larger index, much higher recall on |
| skills whose name/description don't capture every keyword in the body. |
|
|
| - **Version:** 2 |
| - **Corpus:** [`ThakiCloud/SKILLRET`](https://huggingface.co/datasets/ThakiCloud/SKILLRET) (`train+test`) |
| - **Encoder:** [`ThakiCloud/SkillRet-Embedding-0.6B`](https://huggingface.co/ThakiCloud/SkillRet-Embedding-0.6B) |
| - **Skills indexed:** 16783 |
| - **Embedding dim:** 1024 |
| - **Encoded text:** `name + description + body` (truncated to 32768 tokens) |
| - **Normalized:** yes (inner product = cosine similarity) |
|
|
| ## Files |
|
|
| | File | Description | |
| |---|---| |
| | `skill_embeddings.npy` | FP16 numpy array of shape `(16783, 1024)` | |
| | `skill_embeddings_int8.npy` | INT8 per-row quantized array of shape `(16783, 1024)` | |
| | `skill_embeddings_scale.npy` | float32 per-row scale of shape `(16783,)` — reconstruct as `(int8 / 127) * scale` | |
| | `skill_metadata.jsonl` | one JSON record per row, aligned with embeddings (`name`, `description`, `body`, `source_url`, `namespace`, `repo`, `id`) | |
| | `VERSION` | integer version tag; bumped when the corpus, encoder, or encoded-text scheme changes | |
|
|
| ## Usage |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| snapshot_download( |
| repo_id="ThakiCloud/superskillret-index", |
| repo_type="dataset", |
| local_dir="cache/", |
| ) |
| ``` |
|
|
| Downstream consumers should check `VERSION` against their cached copy before reusing local files. |
|
|
