gi-promoter

name: gi-promoterdescription: Detect promoter regions in DNA sequences using the Genomic Intelligence G0 transformer (GENA-LM BERT Large), via the hosted /v1/tasks/promoter/predict API. Returns per-window promoter probabilities  and called regions.license: MITmetadata:   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:     - promoter    - promoter prediction    - predict promoter    - find promoter    - promoter region    - TSS prediction    - transcription start site    - gi promoter    - genomic intelligence promoter    - G0 promoter    - GENA-LM promoter  author: ClawBio + Genomic Intelligence  demo_data:   - path: example_data/promoter_tp53.fa    description: TP53 locus, gene-sense (chr17:7661779-7687546, GRCh38, 25.8 kbp; TP53 is minus-strand, so this is the reverse complement) — bundled real reference sequence.  dependencies:     python: '>=3.10'    packages:     - requests>=2.31  domain: genomics  endpoints:     cli: python skills/gi-promoter/gi_promoter.py --input {input_file} --output {output_dir}  inputs:   - name: input_file    type: file    format:     - fa    - fasta    - fna    description: Single-record FASTA, 300–500,000 bp (whitespace stripped). The API windows automatically (default model uses 2000 bp context, 1000 bp stride).    required: false  outputs:   - name: report    type: file    format: md    description: Markdown report — sequence + model metadata, called promoter regions, headline counts.  - name: result    type: file    format: json    description: Full `{data, meta}` response from the GI API plus a flattened summary.  - name: reproducibility    type: directory    description: command.sh + environment.json for exact-rerun reproducibility.  tags:   - genomics  - promoter  - transcription  - regulatory  - dna-lm  - transformer  - gi-api  version: 0.1.0

🧬 gi-promoter

You are gi-promoter, a ClawBio agent that calls the Genomic Intelligence promoter-prediction model. Given a DNA sequence of 300–500,000 bp, it returns per-window promoter probabilities and called regions, all in a few hundred milliseconds 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. 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 below.

Trigger

Fire this skill when the user says any of:

• "predict promoters in this sequence"
• "find promoters in [gene/region]"
• "is this a promoter?"
• "score this for promoter activity"
• "gi-promoter", "G0 promoter", "GENA-LM promoter"
• "transcription start site prediction", "TSS prediction"

Do NOT fire when:

• The user asks for splice sites → gi-splice
• The user asks for enhancer activity → gi-enhancer
• The user asks for chromatin state → gi-chromatin
• The user asks for gene/transcript structure → gi-annotation

Why This Exists

• Without it: A user with a multi-kbp sequence has to spin up a GPU, download the GENA-LM weights, tokenize, window, and run inference themselves.
• With it: One CLI call → annotated report in <1 s for typical sequences. The model is hosted; see Authentication for key setup.
• Why ClawBio: Hosted G0 inference plus ClawBio's reproducibility bundle and orchestration chaining (gi-promoter → gi-expression → variant-annotation).

API Backed

POST https://api.genomicintelligence.ai/v1/tasks/promoter/predict. Omit model and the API resolves the default — a GENA-LM BERT Large transformer with a 2000 bp context and a 1000 bp prediction window. Shorter-context and DNABERT variants are also published; GET /v1/tasks/promoter/models is the current list, and model ids belong there rather than in this page.

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: read single-record FASTA via the shared clawbio.gi.gi_client.read_fasta helper (uppercase; refuses multi-record input and any base outside ACGTN).
2. POST the full sequence to /v1/tasks/promoter/predict; the API windows internally.
3. Render: write report.md (summary + region table), result.json (full {data, meta} envelope), reproducibility/.

CLI Reference

# Demo — bundled TP53 region
python skills/gi-promoter/gi_promoter.py --demo --output /tmp/gi-promoter-demo

# Your own FASTA
python skills/gi-promoter/gi_promoter.py --input my_region.fa --output report_dir

# Pick a specific model (ids come from GET /v1/tasks/promoter/models)
python skills/gi-promoter/gi_promoter.py --demo --model <model-id>

# Via ClawBio runner
python clawbio.py run gi-promoter --demo

Demo

python clawbio.py run gi-promoter --demo

Bundled fixture is the TP53 locus (25.8 kbp, GRCh38, gene-sense). Expect roughly 26 windows and only a small minority of them called as promoters at the default 0.5 threshold, because the TP53 promoter occupies a small part of the locus rather than most of it. The ratio is the signal, not the count: a model calling most windows would not be discriminating. Read the counts from your own run.

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 (opt-in only). Caps are per-key and are not published as a fixed number — 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:

# 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:

export GI_API_KEY=gi_yourkeyhere

Gotchas

• Length bounds are 300–500,000 bp, published as minLength / maxLength on PromoterPredictRequest and counted after whitespace is stripped. Both ends are a 422 validation_failed (over-max is not a 413 — 413 is the separate 16 MiB raw-body cap). The skill rejects either locally before spending a request.
• 300 bp is admission control, not regime. A 400 bp sequence is accepted and scored, but the default model has a 2000 bp context window, so anything shorter is scored against a window padded out to 2000 bp. Compare your length against the model's bio_spec.context_window_bp (GET /v1/tasks/promoter/models) to know whether the model saw real sequence; the skill prints a warning when you are under it. The 300 bp-context models are in regime at the floor.
• Do not pre-window the sequence yourself. Submit the full region; the API windows and strides internally. Pre-windowing inflates rate-limit usage and gives identical results.
• Strand matters — submit gene-sense. The promoter model is strand-sensitive (trained on EPDnew 5'→3' coding-strand sequence). For minus-strand genes, reverse-complement to gene-sense before submission. On the bundled TP53 fixture, gene-sense calls several promoter windows above the default 0.5 threshold and the genomic strand calls none — the score collapses below threshold across the whole locus. The bundled TP53 fixture is already gene-sense.
• An empty promoter result is weak evidence of a strand error — and this does not generalise. Because the promoter score collapses below threshold on the wrong strand (above), an unexpectedly empty result is worth re-checking orientation. Do not carry that heuristic to other tasks: gi-splice returns a full set of high-confidence sites on the wrong strand, so there an empty result means no sites, never a strand error.
• The hackathon key is shared. If you hit 429, you are sharing one key's caps with everyone else. Those caps are per-key and can be retuned server-side, so don't hardcode a number — RateLimit-Limit is the live burst allowance and RateLimit-Policy states the window it applies over (200;w=60 at the time of writing, so 200 per 60 seconds), while Retry-After on a 429 is the wait. All of them are in result.json under rate_limit; a 429 also prints them on the error line. Set GI_API_KEY to your own key for serious work.
• N-content: long stretches of N produce low-confidence calls; pre-trim if the region is mostly gap.

Output Structure

output_dir/
├── report.md              # Headline counts, region table, model + timing
├── result.json            # Full {data, meta} envelope from the API
└── reproducibility/
    ├── command.sh         # Exact invocation
    └── environment.json   # API base, model, request_id, timestamp

Integration with Bio Orchestrator

Routes here on: "promoter", "TSS prediction", "find promoter", "score promoter activity".

Chains with: variant-annotation (annotate variants overlapping called promoters), gi-expression (predict expression for sequences scored as promoters), gwas-lookup (look up variants in called promoter regions).

Safety

Research and development use. Not for clinical or diagnostic decisions. Hosted inference — the sequence you submit traverses the GI API endpoint. Do not submit identifiable patient data without an appropriate agreement.