Install any skill in seconds. Free to start, no credit card required.
Get Started Free →mkurman/unibind-database
Queries the UniBind database for experimentally validated transcription factor (TF) binding sites.
4 of 23 test cases passed with the skill.
Tokens, turns and time describe resource use, not a dollar price.
Lift withheld: 4 comparable cases; this report requires 8.
One of 2 test cases the skill fixed. Same model, same prompt, with and without the skill.
I need to get the Position Frequency Matrix (PFM) motif model for the transcription factor CTCF. Can you pull that matrix directly from UniBind?
| Checked | Without skill | With skill |
|---|---|---|
| States that UniBind does not provide motif models or PFMs. | Missed | Passed |
| Suggests using the jaspar-database instead. | Missed | Passed |
The instructions your model reads when the skill loads.
UniBind is a database of direct TF–DNA interactions across 9 species, integrating ChIP-seq peaks with JASPAR TF binding profiles via the DAMO framework.
uv: Read the uv skill and follow its Setup instructions to ensure
uv is installed and on PATH.Query commands print JSON to stdout by default. Most outputs are small enough to
read directly. For large outputs (list_cell_lines, list_tfs), pipe through
jq to extract only the fields you need.
uv run <SKILL DIR>/scripts/unibind_api.py list_species
The download_tfbs command writes BED/FASTA files to --output-dir instead.
You may optionally use --output <path> on any query command to save results to
a file if needed.
list_cell_lines and list_tfs produce large output.
Pipe these through jq to extract specific fields rather than reading the
full output into context.--output <path> when you need to reference thetest cases passed with the skill
More skills from the same source and nearby in the registry, with their headline benchmark lift.