Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →mkurman/lancedb
LanceDB — serverless vector database for AI. Columnar storage on Lance format, zero-copy access, multimodal search (text + images + audio), and direct DataFrame integration. No separate server.
Passed 20 of 22 test cases with the skill, and 19 of 22 without it.
1 fixed19 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
A test case the skill fixed. Same model, same prompt, with and without the skill.
In LanceDB Python API, what is the table creation call signature when passing raw initial rows versus when passing a model schema?
| Checked | Without skill | With skill |
|---|---|---|
| Passing initial rows uses positional arguments for table name and data list. | Missed | Passed |
| Passing a model class uses the schema keyword argument. | Passed | Passed |
The instructions your model reads when the skill loads.
LanceDB is a developer-friendly, serverless vector database built on the Lance columnar format. It supports multimodal search (text, image, audio embeddings), hybrid search, and efficient streaming ingestion without a separate server process.
uv pip install lancedb
import lancedb
import numpy as np
db = lancedb.connect("./my_lancedb")
table = db.create_table("vectors", [
{"vector": np.random.rand(128), "text": "hello world"},
{"vector": np.random.rand(128), "text": "goodbye moon"},
])
results = table.search(np.random.rand(128)).limit(5).to_list()
print([r["text"] for r in results])
import lancedb
from lancedb.embeddings import with_open_clip
@with_open_clip
class Images:
image: str
vector: list
table = db.create_table("images", schema=Images)
table.add([{"image": "photo.jpg"}, {"image": "diagram.png"}])
results = table.search("sunset landscape").limit(3).to_pandas()
test cases passed, vs 19 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.