Agent skill

Gi Promoter

by ClawBio in ClawBio/ClawBio

Detect promoter regions in DNA sequences using the Genomic Intelligence G0 transformer (GENA-LM BERT Large), via the hosted /v1/tasks/promoter/predict API.

MITAuto-check: notesResearch & Science

Install Gi Promoter

skills CLI
$ npx skills add ClawBio/ClawBio --skill gi-promoter -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ClawBio/ClawBio gi-promoter --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ClawBio/ClawBio.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/gi-promoter .claude/skills/gi-promoter && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
gi-promoter
GitHub stars
1.2k
Token cost
~2.6k tokens
SKILL.md length
1,011 words
Files
6
Skills in repo
104
Repo updated
First seen
Licence
MIT

At a glance

Detect promoter regions in DNA sequences using the Genomic Intelligence G0 transformer (GENA-LM BERT Large), via the hosted /v1/tasks/promoter/predict API.

  • Works in 3 steps: Parse: read single-record FASTA via the… → POST the full sequence to… → Render: write report.md (summary +…
  • Tasks that involve Bioinformatics
  • SKILL.md covers Trigger, Why This Exists, API Backed and Workflow, plus 7 more sections
  • Runs Python scripts from its folder; calls python; reaches api.genomicintelligence.ai; needs GI_API_KEY

What it does

Gi Promoter is an agent skill from ClawBio/ClawBio. 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.

Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files (for example `api.py`, `gi_promoter.py` and `tests/__init__.py`).

It sits in Research & Science, covering Bioinformatics. The repository describes itself as: 🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first. Reproducible. Open. Free. The licence is MIT.

When your agent uses it

  • Tasks that involve Bioinformatics

Example prompts

  • “/gi-promoter”

Requirements

  • Python 3
  • A credential in GI_API_KEY

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Parse: read single-record FASTA via the shared clawbio.gi.gi_client.read_fasta helper (uppercase; refuses multi-record input and any base…
  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/.

What it can do on your machine

Read from SKILL.md and the folder at commit dece754. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • api.genomicintelligence.ai

    Also links to:

    • genomicintelligence.ai

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • GI_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Gi Promoter loads about 2.6k tokens when it runs. Until then it costs about 57 tokens; SKILL.md has 1,011 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~57
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:156
    cp .env.example .env
  • NoteMentions a .env fileSKILL.md:157
    set -a && source .env && set +a

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ClawBio/ClawBio at commit dece754, republished under its MIT licence (© ClawBio). 1,011 words, ~2,601 tokens.

Download SKILL.mdSave it as .claude/skills/gi-promoter/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
gi-promoter
description
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
MIT
metadata.author
ClawBio + Genomic Intelligence
metadata.domain
genomics
metadata.tags
genomics, promoter, transcription, regulatory, dna-lm, transformer, gi-api
metadata.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

bash
# 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

bash
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:

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
Show full SKILL.md (452 more words)Show less

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.

© ClawBio, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files in skills/gi-promoter of ClawBio/ClawBio.

  • SKILL.md
  • api.py
  • example_data/promoter_tp53.fa
  • gi_promoter.py
  • tests/__init__.py
  • tests/test_gi_promoter.py

Open the folder on GitHubat commit dece754

Compare with similar skills

Gi Promoter next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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13C Metabolic Flux AnalysisK-Dense-AI/scientific-agent-skills48k1 repos~3.2kAutomated safety check: PassMIT
Clinvar Databasegoogle-deepmind/science-skills3.2k2 repos~3.9kAutomated safety check: NotesApache-2.0
Metabolic Study Planneraiming-lab/AutoResearchClaw15k—~1.9kAutomated safety check: PassMIT
Dbsnp Databasegoogle-deepmind/science-skills3.2k2 repos~3.4kAutomated safety check: NotesApache-2.0

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Questions about Gi Promoter

What does Gi Promoter do?

Detect promoter regions in DNA sequences using the Genomic Intelligence G0 transformer (GENA-LM BERT Large), via the hosted /v1/tasks/promoter/predict API. Gi Promoter is an agent skill from ClawBio/ClawBio. Detect promoter regions in DNA sequences using the Genomic Intelligence G0 transformer (GENA-LM BERT Large), via the hosted /v1/tasks/promoter/predict API.

When should I use Gi Promoter?

Gi Promoter fits situations like: tasks that involve Bioinformatics.

How do I install Gi Promoter in Claude Code?

Run `npx skills add ClawBio/ClawBio --skill gi-promoter -a claude-code`. Or copy the skill folder (skills/gi-promoter in ClawBio/ClawBio) into .claude/skills/gi-promoter in your project. Claude Code loads it when a task matches its description.

How do I install Gi Promoter in Codex?

Run `npx skills add ClawBio/ClawBio --skill gi-promoter -a codex`. Or copy the skill folder (skills/gi-promoter in ClawBio/ClawBio) into .agents/skills/gi-promoter in your project. Codex loads it when a task matches its description.

Can I use Gi Promoter in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ClawBio/ClawBio --skill gi-promoter -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/gi-promoter, .gemini/skills/gi-promoter, .github/skills/gi-promoter and .opencode/skills/gi-promoter in your project.

What does Gi Promoter need to run?

Going by SKILL.md and its folder, Gi Promoter needs Python for the scripts in its folder, the command-line tools its instructions call (python) and credentials named GI_API_KEY. Our summary lists: Python 3; A credential in GI_API_KEY.

Does Gi Promoter access the network?

SKILL.md names 2 domains. In commands or code: api.genomicintelligence.ai; the agent is likely to contact it when it follows the instructions. As links in the text: genomicintelligence.ai. This is read from the text; nothing was executed.

Is Gi Promoter safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Gi Promoter use?

Gi Promoter is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Gi Promoter use?

About 2.6k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Gi Promoter?

Skills that share tags, products or a category with Gi Promoter: Alphagenome Single Variant Analysis (google-deepmind/science-skills, 3.2k stars), 13C Metabolic Flux Analysis (K-Dense-AI/scientific-agent-skills, 48k stars), Clinvar Database (google-deepmind/science-skills, 3.2k stars) and Metabolic Study Planner (aiming-lab/AutoResearchClaw, 15k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Gi Promoter?

ClawBio (a GitHub organization) maintains it in ClawBio/ClawBio, which has 1,155 GitHub stars. The repository holds 104 skills in this directory. The repository was last updated on October 9, 2026.

Source: ClawBio/ClawBio on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.