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/gi-chromatin

command.sh + environment.json.

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clawbio
1.1k99 skills4 commands
Install
$ npx -y skills add ClawBio/ClawBio --skill gi-chromatin --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/gi-chromatin

Context preview

The summary Claude sees to decide when to auto-load this skill.

command.sh + environment.json.

SKILL.md

gi-chromatin.SKILL.md
name: gi-chromatin
description: Predict chromatin state — histone marks, DNase, TF binding — across 919 tracks (DeepSEA-style) for DNA sequences, via the hosted Genomic Intelligence /v1/tasks/chromatin/predict API.
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:
    - chromatin
    - chromatin state
    - chromatin annotation
    - histone mark
    - histone modification
    - DNase
    - ATAC
    - TF binding
    - transcription factor binding
    - DeepSEA
    - epigenome
    - gi chromatin
    - genomic intelligence chromatin
  author: ClawBio + Genomic Intelligence
  demo_data:
  - path: example_data/chromatin_active_promoter_chr19.fa
    description: Chr19 active-promoter region — bundled real human reference sequence.
  dependencies:
    python: '>=3.10'
    packages:
    - requests>=2.31
  domain: genomics
  endpoints:
    cli: python skills/gi-chromatin/gi_chromatin.py --input {input_file} --output {output_dir}
  inputs:
  - name: input_file
    type: file
    format:
    - fa
    - fasta
    - fna
    description: Single-record FASTA, 200–500,000 bp (whitespace stripped); the API windows automatically.
    required: false
  outputs:
  - name: report
    type: file
    format: md
    description: Markdown report — windows processed, total annotations across tracks, model + timing.
  - name: result
    type: file
    format: json
    description: Full `{data, meta}` response with per-window per-track predictions.
  - name: reproducibility
    type: directory
    description: command.sh + environment.json.
  tags:
  - genomics
  - chromatin
  - histone
  - DNase
  - ATAC
  - TF-binding
  - deepsea
  - dna-lm
  - gi-api
  version: 0.1.0

🧶 gi-chromatin

You are **gi-chromatin**, a ClawBio agent that calls the **Genomic Intelligence** chromatin-annotation model (DeepSEA-style, 919 tracks: histone marks + DNase + TF binding across ENCODE cell types).

> ⚠️ **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](#authentication) below.

Trigger

**Fire this skill when the user says any of:**

  • "predict chromatin state for this sequence"
  • "histone mark prediction", "DNase prediction", "ATAC prediction"
  • "TF binding prediction"
  • "DeepSEA"
  • "gi-chromatin", "predict epigenome"
  • "is this region accessible?"

**Do NOT fire when:**

  • The user asks specifically about enhancer activity → `gi-enhancer`
  • The user asks for promoter prediction → `gi-promoter`

Why This Exists

  • **Without it**: Running DeepSEA / similar locally needs custom torch envs + weight wrangling.
  • **With it**: One CLI call → 919 track predictions per window, in seconds.
  • **Why ClawBio**: Hosted G0 DeepSEA inference plus ClawBio reproducibility and chaining.

API Backed

`POST https://api.genomicintelligence.ai/v1/tasks/chromatin/predict`. Omit `model` and the API resolves the default — a 919-track DeepSEA-style prediction head. `GET /v1/tasks/chromatin/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/chromatin/predict`. 3. **Render**: `report.md` (window + total-annotation counts; per-track detail in `result.json`).

CLI Reference

python skills/gi-chromatin/gi_chromatin.py --demo --output /tmp/gi-chromatin-demo
python skills/gi-chromatin/gi_chromatin.py --input my_region.fa --output report_dir
python clawbio.py run gi-chromatin --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 (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

Demo

python clawbio.py run gi-chromatin --demo

Bundled fixture is an active-promoter region from chr19. Expect dense annotation across active-promoter tracks (H3K4me3, H3K27ac, DNase, etc.) and many called windows.

Gotchas

  • **Big response.** 919 tracks × N windows → multi-MB `result.json`. The report.md summarizes; mine `result.json` programmatically for specific tracks.
  • **Track labels are in the response.** Do not hardcode track indices — read the names from `data.tracks`.
  • **Length bounds are 200–500,000 bp**, published as `minLength` /
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