genomic-intelligence – skill Dữ liệu & Khoa học cho agent AI

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](https://docs.genomicintelligence.ai) ·

REST contract at [api.genomicintelligence.ai/v1/openapi.json](https://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.

> Research and development use. Not for clinical or diagnostic decisions.

Two ways to call GI

Hosted MCP server (keyless; preferred on MCP hosts)

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 rate- and concurrency-limited public demo tier, and an optional gi_ bearer

key raises those limits. It exposes acquisition tools that return a sequence handle

(sequence_ref) and predict_* tools that take that handle, so large sequences

stay out of the context. See [MCP workflow](#mcp-workflow-handle-based) below and

references/mcp.md.

REST API (universal)

Plain HTTP with requests against https://api.genomicintelligence.ai/v1. The

REST path requires a GI_API_KEY (a gi_ bearer). Use it on any host, in

scripts, or when you need the raw envelope. See [Core REST workflow](#core-rest-workflow).

Access and authentication

1. The hosted MCP demo is keyless — try it with nothing set.

2. REST prediction and job operations need a key, sent as Authorization: Bearer <key>.

Public GET /v1/tasks/{task}/models discovery needs no key and is rate-limited

by source IP; inspect model windows and bounds before requesting access.

See the [current authentication contract](https://docs.genomicintelligence.ai/).

Request a prediction key at [[email protected]](mailto:[email protected]).

3. Never hardcode the key. Read it from the GI_API_KEY environment variable

(or a .env via python-dotenv). Never commit keys.

export GI_API_KEY="gi_yourkeyhere"     # optional for MCP; required for REST
export GI_BASE_URL="https://api.genomicintelligence.ai"   # override for staging

Keys are scoped to a partner tier with concurrency and per-minute caps. A 429

means you hit a cap — back off and retry, or ask GI to raise your tier.

The six tasks

Each task is its own published operation with its own request schema, its own

minimum length, and its own closed options object — `POST

/v1/tasks/promoter/predict, /v1/tasks/splice/predict`,

/v1/tasks/enhancer/predict, /v1/tasks/chromatin/predict,

/v1/tasks/annotation/predict, /v1/tasks/expression/predict. Each path is a

literal string, so nothing needs to be constructed, and there is no shared

PredictRequest schema. Body is `{sequence, sequence_name?, model?,

options?}, returning a {data, meta}` envelope. What differs per task:

| Task | Recommended mode | Accepted length | context_window_bp | Notes |

|---|---|---|---|---|

| promoter | sync | 300–500,000 bp | 2,000 bp | sliding-window promoter regions |

| splice | sync | 100–500,000 bp | 15,000 bp | donor/acceptor sites (long-context BigBird); strand-specific — feed transcript orientation |

| enhancer | sync | 50–500,000 bp | 249 bp | dev + housekeeping scores (DeepSTARR, *Drosophila*) |

| chromatin | sync | 200–500,000 bp | 1,000 bp | hundreds of tracks (DeepSEA) |

| expression | sync | 9,198–500,000 bp | n/a (trained_window_bp 9,198) | log(TPM+1); needs tss_index unless exactly 9,198 bp, plus a cell-type description |

| annotation | async | 1,000–500,000 bp | n/a | de-novo transcripts; submit + poll; sync JSON above 200,000 bp is 413 sync_too_large |

Recommended mode is guidance, not a constraint — every task accepts both. Omit Prefer for a synchronous 200; send Prefer: respond-async for a 202 plus GET /v1/tasks/jobs/{job_id}. The one enforced limit is per operation: where /v1/openapi.json publishes x-sync-limit-bp on a POST, a synchronous JSON request above that length is 413 sync_too_large — 200,000 bp on annotation and 50,000 bp on the composite workflow in contract revision 16. Read the field rather than memorising the numbers. Annotation BED/GFF3 stays synchronous at any admitted length and can time out; the other five predict tasks have no hard sync cap.

The minimum is admission control, not regime. A request above the floor but

shorter than the selected model's bio_spec.context_window_bp is *accepted and

scored* — against a window padded out to the context window. Enhancer is the

sharp case: the floor is 50 bp but the context window is 249 bp, so 50–248 bp is

scored mostly on padding. Compare your length against

context_window_bp from GET /v1/tasks/{task}/models to know whether the model

saw real sequence. Longer-than-context input is fine — the scanner steps a

prediction window at a time and pads only the final partial window.

Under the floor and over the 500,000 bp cap are both 422 validation_failed

at loc ["body","sequence"]; over-length is *not* a 413. All lengths are

measured after whitespace is stripped, so a line-wrapped FASTA body can be pasted

verbatim (a > header line still fails the alphabet check).

options is typed and closed (additionalProperties: false) per task — an

unknown key is a hard 422 validation_failed with type: "extra_forbidden",

never ignored:

| Task | options keys |

|---|---|

| promoter | threshold (0–1, default 0.5) |

| splice | threshold (0–1, default 0.5), site_types (subset of ["donor","acceptor"], default both) |

| enhancer | *(none)* |

| chromatin | threshold (0–1, default 0.5) |

| annotation | batch_size (1–128, default 8), shift_coordinates, reverse_complement (default true) |

| expression | description — required, and the only key |

Prefer: respond-async is a declared header on all six predict operations

and on the composite, not just annotation — see [Async](#async-any-task-recommended-for-annotation).

Omit model and the API uses the task's default — that is the recommended

call. Default model IDs are intentionally not documented here: defaults

change and retired IDs fail hard, so never hardcode one. To pin a model, or to

pick a non-human one (Drosophila, yeast, and Arabidopsis models exist for several

tasks), discover IDs at call time with GET /v1/tasks/{task}/models (REST) or

list_models (MCP) — and never invent one. Full per-task output shapes are

in references/tasks.md.

expression is the strictest of the six: alone among them its schema requires

options as well as sequence. Three hard rules it enforces — every violation

is a 422, nothing is padded or clamped, and there is no opt-out flag, header,

or query parameter:

• It always scores exactly one 9,198 bp TSS-centred window —

sequence[tss_index-4599 : tss_index+4599]. The endpoint itself accepts

9,198–500,000 bp; anything below 9,198 bp is rejected outright.

• tss_index is required unless the sequence is exactly 9,198 bp. It is the

0-based TSS offset into the whitespace-stripped sequence, bounded by

4599 ≤ tss_index ≤ len(sequence) − 4599. At exactly 9,198 bp it defaults to

4,599, the only legal value there. So you may submit a whole locus (up to

500 kb) and let the server cut the window — but the server does not

discover the TSS for you (that is the composite workflow's job), and does

not reverse-complement: submit gene-sense sequence.

• options.description — a cell-type / assay string (e.g. "K562 cells") —

is required, and is the only key expression accepts inside options.

Unknown top-level body fields are rejected too.

> Note: the legal tss_index range is wide, so an offset that is merely

> *wrong* (counted over raw FAS

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