Agent skill · research science · k-dense-ai
genomic-intelligence
Predict regulatory features, gene structure, and expression directly from DNA sequence using Genomic Intelligence's hosted transformer DNA language models — no local GPU or model weights. Six tasks over a REST API and a hosted MCP server (keyless public demo): promoter regions, splice donor/acceptor sites, enhancer activity, chromatin state, sequence-to-expression (log TPM), and de-novo gene annotation, plus a composite find-genes-then-predict-expression workflow. Use when the user has a gene symbol, a genomic region, or a DNA/FASTA sequence and wants any of these predictions, mentions Genomic Intelligence, genomicintelligence.ai, api.genomicintelligence.ai, or mcp.genomicintelligence.ai.
Why this skill is useful
Provides access to a hosted API for genomic predictions that the AI cannot generate on its own, including specific tasks like promoter prediction and splice site identification.
What it needs
Requires genomicintelligence account access. About 6k tokens when loaded. Last updated 2026-08-03. 32,849 stars on the source repository.
What this skill does
Genomic Intelligence — DNA Sequence Models Genomic Intelligence (GI) serves transformer DNA language models over six sequence-analysis tasks on managed GPUs. Give it a gene symbol, a genomic region, or a DNA/FASTA sequence; it returns structured predictions — promoter regions, splice sites, enhancer activity, chromatin state, expression (log TPM), and de-novo gene annotation. Nothing runs locally: no model weights, no GPU, no heavy Python stack. It is a thin client over a hosted, versioned inference API. Official docs: docs.genomicintelligence.ai · REST contract at api.genomicintelligence.ai/v1/openapi.json · hosted MCP server at https://mcp.genomicintelligence.ai/mcp When to use this skill Use GI when the user has DNA and wants a model prediction: Find promoters in a genomic region (promoter) Predict splice donor/acceptor sites (splice) Score enhancer activity — developmental & housekeeping (enhancer) Annotate chromatin state across hundreds of tracks (chromatin) Predict expression as log(TPM+1) from a sequence + cell-type context (expression) Annotate genes/transcripts de novo, no reference needed (annotation) Find the genes in a region and predict each one's expression (composite) Not for local alignment, variant calling, or file I/O — use a local tool (BioPython, bcftools) for those. GI is for model inference from sequence. For research and development use, not clinical or diagnostic decisions. Two ways to call GI Hosted MCP server (best for AI agents — keyless) GI hosts an MCP server at https://mcp.genomicintelligence.ai/mcp (Streamable HTTP). When your agent host supports MCP, prefer it: it works keyless against a capped public demo quota (zero setup), and an optional gi bearer key raises the quota. It exposes acquisition tools that return a sequence handle (sequenceref) and predict tools that take that handle — so large sequences never bloat the context. See MCP workflow below and references/mcp.md. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills k-dense-ai/genomic-intelligence