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Get Started Free →clawbio/archaic-introgression
Detect Neanderthal and Denisovan introgression segments from modern human genomes
Passed 18 of 20 test cases with the skill, and 8 of 20 without it.
and 12 more in the full report
11 fixed9 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 9 test cases the skill fixed. Same model, same prompt, with and without the skill.
What are the exact file names created in the specified output directory `/tmp/introgression` for the machine-readable summary report and the genomic coordinate track?
| Checked | Without skill | With skill |
|---|---|---|
| Names introgression_results.json as the JSON report file. | Missed | Passed |
| Names segments.bed as the genomic track file. | Missed | Passed |
The instructions your model reads when the skill loads.
Fire when:
Do NOT fire when:
Between 1-4% of non-African modern human genomes derive from archaic hominins (Neanderthals, Denisovans). Identifying these segments matters for understanding human evolution, disease susceptibility, and immune adaptation. Three complementary methods exist (IBDmix, Sprime, hmmix), each with different strengths. This skill wraps all three behind a unified interface with a pure-Python fallback when external binaries are unavailable.
One skill, one task: detect and report archaic introgression segments. Does not perform downstream functional annotation of introgressed variants (chain with vcf-annotator for that).
test cases passed, vs 8 / 20 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.