Predict enhancer activity in DNA sequences using the Genomic Intelligence G0 DeepSTARR model, via the hosted /v1/tasks/enhancer/predict API. Returns per-window activity scores.
Scanned 9/6/2026
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---
name: gi-enhancer
description: Predict enhancer activity in DNA sequences using the Genomic Intelligence G0 DeepSTARR model, via the hosted /v1/tasks/enhancer/predict API. Returns per-window activity scores.
license: MIT
metadata:
openclaw:
requires:
bins:
- python3
env: null
config: null
always: false
emoji: 🎚️
homepage: https://docs.genomicintelligence.ai
os:
- darwin
- linux
install:
- kind: pip
package: requests
bins: null
trigger_keywords:
- enhancer
- enhancer activity
- predict enhancer
- regulatory element
- cis-regulatory
- CRE
- DeepSTARR
- STARR-seq
- massively parallel reporter assay
- MPRA
- gi enhancer
- genomic intelligence enhancer
author: ClawBio + Genomic Intelligence
demo_data:
- path: example_data/enhancer_eve.fa
description: Drosophila eve (even-skipped) developmental-enhancer region (chr2R:9972000-9982000, BDGP6, gene-sense, incl. upstream stripe enhancers) — canonical DeepSTARR benchmark.
dependencies:
python: '>=3.10'
packages:
- requests>=2.31
domain: genomics
endpoints:
cli: python skills/gi-enhancer/gi_enhancer.py --input {input_file} --output {output_dir}
inputs:
- name: input_file
type: file
format:
- fa
- fasta
- fna
description: Single-record FASTA (any length; API windows automatically).
required: false
outputs:
- name: report
type: file
format: md
description: Markdown report — windows processed, max predicted activity, model + timing.
- name: result
type: file
format: json
description: Full `{data, meta}` response.
- name: reproducibility
type: directory
description: command.sh + environment.json.
tags:
- genomics
- enhancer
- regulatory
- cis-regulatory
- deepstarr
- dna-lm
- gi-api
version: 0.1.0
---
# 🎚️ gi-enhancer
You are **gi-enhancer**, a ClawBio agent that calls the **Genomic Intelligence** enhancer-activity model. Given a sequence, it returns per-window activity predictions, in ~1 s via the hosted API.
> ⚠️ **Remote inference — opt-in required.** Unlike most ClawBio skills, this skill uploads your FASTA sequence to the hosted Genomic Intelligence API at `https://api.genomicintelligence.ai`. Prefer a browser? The same models run interactively at <https://genomicintelligence.ai>. **Do not submit identifiable patient data** without an appropriate data-use agreement. Key setup: see [Authentication](#authentication) below.
## Trigger
**Fire this skill when the user says any of:**
- "predict enhancer activity"
- "score this for enhancer / CRE / regulatory function"
- "is this an enhancer?"
- "DeepSTARR prediction", "STARR-seq prediction"
- "gi-enhancer"
- "predict cis-regulatory activity"
**Do NOT fire when:**
- The user asks for promoter activity → `gi-promoter`
- The user asks for chromatin state / accessibility → `gi-chromatin`
## Why This Exists
- **Without it**: DeepSTARR-style local inference requires Keras + GPU + tokenization knowhow.
- **With it**: One CLI call → per-window activity scores in ~1 s.
- **Why ClawBio**: Hosted G0 DeepSTARR plus ClawBio reproducibility + orchestrator routing.
## API Backed
`POST https://api.genomicintelligence.ai/v1/tasks/enhancer/predict` — default model `g0-deepstarr`.
## Workflow
1. **Parse**: single-record FASTA.
2. **POST** to `/v1/tasks/enhancer/predict`; the API windows internally.
3. **Render**: `report.md` + `result.json` + `reproducibility/`.
## CLI Reference
```bash
python skills/gi-enhancer/gi_enhancer.py --demo --output /tmp/gi-enhancer-demo
python skills/gi-enhancer/gi_enhancer.py --input my_region.fa --output report_dir
python clawbio.py run gi-enhancer --demo
```
## Authentication
The skill requires a Genomic Intelligence partner key in `GI_API_KEY`. Resolution order:
1. `--api-key <value>` CLI flag (explicit override).
2. `GI_API_KEY` environment variable.
3. Otherwise: the skill raises a `RuntimeError` pointing here.
### Quick start — ClawBio hackathon key
A shared hackathon-tier key ships in `.env.example` at the repo root (50 concurrent / 120 rpm, opt-in only). From wherever the ClawBio files live on your machine:
```bash
# Repo root (git clone) — or ~/.claude/plugins/cache/clawbio/clawbio/<version>/ for plugin installs
cp .env.example .env
set -a && source .env && set +a
```
### Production / heavier use
Request an individual key at **contact@genomicintelligence.ai**, then:
```bash
export GI_API_KEY=gi_yourkeyhere
```
## Demo
```bash
python clawbio.py run gi-enhancer --demo
```
Bundled fixture is the Drosophila *eve* (even-skipped) locus (chr2R:9972000-9982000, incl. the upstream stripe enhancers) — the canonical DeepSTARR benchmark for developmental enhancer activity. Expect a positive developmental signal (max dev ~2.1).
## Gotchas
- **DeepSTARR was trained on Drosophila S2 cells.** Activity scores for mammalian sequences are still informative as a relative ranking, but the absolute scale is calibrated for fly chromatin.
- **Pre-windowing is unnecessary** — the API strides internally.
- **Hackathon key is shared** — `GI_API_KEY` for heavier use.
## Output Structure
```
output_dir/
├── report.md
├── result.json
└── reproducibility/
├── command.sh
└── environment.json
```
## Integration with Bio Orchestrator
Routes here on: "enhancer", "DeepSTARR", "STARR-seq", "predict CRE", "regulatory activity".
Chains with: `gi-promoter` (joint regulatory-element scan), `gi-chromatin` (cross-validate with chromatin accessibility), `variant-annotation` (variants overlapping high-activity windows).
## Safety
Research tool. Not a clinical assay.
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