Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/synthetic-sciences/openscience/dnanexus-integrationnpx skills add synthetic-sciences/openscience --skill dnanexus-integrationgit clone --depth 1 https://github.com/synthetic-sciences/openscienceWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/synthetic-sciences/openscience/dnanexus-integration)<a href="https://agentmods.dev/skills/synthetic-sciences/openscience/dnanexus-integration"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/dnanexus-integration.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00049 | $0.02413 |
| Opus 5 | $0.00024 | $0.01207 |
| Sonnet 5 | $0.00010 | $0.00483 |
| Haiku 4.5 | $0.00005 | $0.00241 |
Grade A, and why
dnanexus-integration scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
subprocess.check_call([ Copies of this mod
8 near-identical copies found in the catalogue:
- dnanexus-integration — 98% identical, 3 lines differ
- dnanexus-integration — 98% identical, 8 lines differ
- dnanexus-integration — 98% identical, 3 lines differ
- dnanexus-integration — 98% identical, 8 lines differ
- dnanexus-integration — 95% identical, 4 lines differ
- dnanexus-integration — 88% identical, 6 lines differ
- dnanexus-integration — 88% identical, 6 lines differ
- dnanexus-integration — 86% identical, 5 lines differ
How it starts
The opening of the file, as written. The whole thing — 383 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DNAnexus Integration
Overview
DNAnexus is a cloud platform for biomedical data analysis and genomics. Build and deploy apps/applets, manage data objects, run workflows, and use the dxpy Python SDK for genomics pipeline development and execution.
When to Use This Skill
This skill should be used when:
- Creating, building, or modifying DNAnexus apps/applets
- Uploading, downloading, searching, or organizing files and records
- Running analyses, monitoring jobs, creating workflows
- Writing scripts using dxpy to interact with the platform
- Setting up dxapp.json, managing dependencies, using Docker
- Processing FASTQ, BAM, VCF, or other bioinformatics files
- Managing projects, permissions, or platform resources
Core Capabilities
The skill is organized into five main areas, each with detailed reference documentation:
1. App Development
Purpose: Create executable programs (apps/applets) that run on the DNAnexus platform.
Key Operations:
- Generate app skeleton with
dx-app-wizard - Write Python or Bash apps with proper entry points
- Handle input/output data objects
- Deploy with
dx buildordx build --app - Test apps on the platform
Common Use Cases:
- Bioinformatics pipelines (alignment, variant calling)
- Data processing workflows
- Quality control and filtering
- Format conversion tools
Reference: See references/app-development.md for:
- Complete app structure and patterns
- Python entry point decorators
- Input/output handling with dxpy
- Development best practices
- Common issues and solutions
2. Data Operations
Purpose: Manage files, records, and other data objects on the platform.
Key Operations:
- Upload/download files with
dxpy.upload_local_file()anddxpy.download_dxfile() - Create and manage records with metadata
- Search for data objects by name, properties, or type
- Clone data between projects
- Manage project folders and permissions
Common Use Cases:
- Uploading sequencing data (FASTQ files)
- Organizing analysis results
- Searching for specific samples or experiments
- Backing up data across projects
- Managing reference genomes and annotations
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 383 lines · 49 tokens per session scan A bb84d8f6a053
dnanexus-integration is a skill published in the GitHub repository synthetic-sciences/openscience (3,432 stars, last pushed today), licensed Apache-2.0. It adds 49 tokens to every session and 2,413 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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