Build a research plan
Turn an open question into a bounded research plan with credible sources and decision criteria.
5,425,473 AI resources indexedWorking toward the worldβs largest AI resource index.
Predicts enhancer activity in DNA sequences using the Genomic Intelligence model, providing quick per-window activity scores.
---
name: gi-enhancer-ef37379491be
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: ποΈ
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) β 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, 50β500,000 bp (whitespace stripped); the API windows automatically.
required: false
outputs:
- name: report
type: file
format: md
description: Markdown report β 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
---
# ποΈ 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.
> β οΈ **Remote inference β opt-in required.** Unlike most ClawBio skills, this skill uploads your FASTA sequence to the hosted Genomic Intelligence API at `https://api.genomicintelligence.ai`. The same models also 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 β `gi-promoter`
- The user asks for chromatin state / accessibility β `gi-chromatin`
## Why This Exists
- **Without it**: DeepSTARR-style local inference requires Keras + GPU + tokenization knowhow.
- **With it**: One CLI call β 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`. Omit `model` and the API resolves the default β a DeepSTARR model trained on *Drosophila* S2 cells. `GET /v1/tasks/enhancer/models` is the current list.
> **Contract note.** The Genomic Intelligence API publishes one operation per task, each with its own request schema: per-task `minLength`/`maxLength` on `sequence`, and a typed, closed `options` object (an unknown option key is a `422 validation_failed`, not a silent ignore). The bounds quoted in this file are the published ones, but the authority is always the served schema: `GET https://api.genomicintelligence.ai/v1/openapi.json`.
## 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 β ClawBio hackathon key
A shared hackathon-tier key ships in `.env.example` at the repo root (opt-in only). Caps are per-key and are not published as a fixed number β read `RateLimit-Limit` / `RateLimit-Remaining` on any `/v1/tasks/` response for the live allowance. The runner keeps them for you: they are in `result.json` under `rate_limit`, and a `429` names them on the error line. From wherever the ClawBio files live on your machine:
```bash
# Repo root (git clone) β 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) β the canonical DeepSTARR benchmark for developmental enhancer activity. Expect a positive developmental signal; read the score from your own run.
## 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.
- **Length bounds are 50β500,000 bp**, published as `minLength` / `maxLength` on `EnhancerPredictRequest` and counted after whitespace is stripped. Both ends are a `422 validation_failed` (over-max is *not* a 413 β 413 is the separate 16 MiB raw-body cap). The skill rejects either locally before spending a request.
- **50 bp is admission control, not a meaningful enhancer size.** It is the strictest floor any enhancer model needs; some models accept less. The models' context window is 249 bp, so 50β248 bp is accepted and scored β against a window padded out to 249 bp. Compare your length against `bio_spec.context_window_bp` (`GET /v1/tasks/enhancer/models`) to know whether the model saw real sequence; the skill warns when you are under it.
- **Pre-windowing is unnecessary** β the API windows and strides internally.
- **Hackathon key is shared** β `GI_API_KEY` for heavier use.
## Output Structure
```
output_dir/
βββ report.md
βββ result.json
βββ reproducibility/
βββ command.sh
βββ 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 and development use. Not for clinical or diagnostic decisions.
---
name: gi-enhancer-ef37379491be
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: ποΈ
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) β 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, 50β500,000 bp (whitespace stripped); the API windows automatically.
required: false
outputs:
- name: report
type: file
format: md
description: Markdown report β 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
---
# ποΈ 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.
> β οΈ **Remote inference β opt-in required.** Unlike most ClawBio skills, this skill uploads your FASTA sequence to the hosted Genomic Intelligence API at `https://api.genomicintelligence.ai`. The same models also 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 β `gi-promoter`
- The user asks for chromatin state / accessibility β `gi-chromatin`
## Why This Exists
- **Without it**: DeepSTARR-style local inference requires Keras + GPU + tokenization knowhow.
- **With it**: One CLI call β 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`. Omit `model` and the API resolves the default β a DeepSTARR model trained on *Drosophila* S2 cells. `GET /v1/tasks/enhancer/models` is the current list.
> **Contract note.** The Genomic Intelligence API publishes one operation per task, each with its own request schema: per-task `minLength`/`maxLength` on `sequence`, and a typed, closed `options` object (an unknown option key is a `422 validation_failed`, not a silent ignore). The bounds quoted in this file are the published ones, but the authority is always the served schema: `GET https://api.genomicintelligence.ai/v1/openapi.json`.
## 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 β ClawBio hackathon key
A shared hackathon-tier key ships in `.env.example` at the repo root (opt-in only). Caps are per-key and are not published as a fixed number β read `RateLimit-Limit` / `RateLimit-Remaining` on any `/v1/tasks/` response for the live allowance. The runner keeps them for you: they are in `result.json` under `rate_limit`, and a `429` names them on the error line. From wherever the ClawBio files live on your machine:
```bash
# Repo root (git clone) β 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) β the canonical DeepSTARR benchmark for developmental enhancer activity. Expect a positive developmental signal; read the score from your own run.
## 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.
- **Length bounds are 50β500,000 bp**, published as `minLength` / `maxLength` on `EnhancerPredictRequest` and counted after whitespace is stripped. Both ends are a `422 validation_failed` (over-max is *not* a 413 β 413 is the separate 16 MiB raw-body cap). The skill rejects either locally before spending a request.
- **50 bp is admission control, not a meaningful enhancer size.** It is the strictest floor any enhancer model needs; some models accept less. The models' context window is 249 bp, so 50β248 bp is accepted and scored β against a window padded out to 249 bp. Compare your length against `bio_spec.context_window_bp` (`GET /v1/tasks/enhancer/models`) to know whether the model saw real sequence; the skill warns when you are under it.
- **Pre-windowing is unnecessary** β the API windows and strides internally.
- **Hackathon key is shared** β `GI_API_KEY` for heavier use.
## Output Structure
```
output_dir/
βββ report.md
βββ result.json
βββ reproducibility/
βββ command.sh
βββ 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 and development use. Not for clinical or diagnostic decisions.
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Includes source scripts; review them before use. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.