Skills dnanexus-integration

📦

dnanexus-integration

Name: dnanexus-integration
Author: davila7

Content revision r2 Medium Risk ⚙️ External commands🔑 Env variables🌐 Network access

Build DNAnexus Genomics Workflows

DNAnexus development requires coordinated app configuration, data handling, and job orchestration. This skill provides practical patterns for building, running, and maintaining genomics workflows.

Supports: Claude Codex Code(CC)

⚠️ 50 Poor

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request

Review the Skillstore skill "dnanexus-integration" from https://skillstore.io/skills/davila7-dnanexus-integration.md and its manifest at https://skillstore.io/api/skills/davila7-dnanexus-integration/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/davila7-dnanexus-integration.md Signed manifest GET /api/skills/davila7-dnanexus-integration/manifest Signed lockfile GET /api/skills/davila7-dnanexus-integration/lockfile

Test it

Using "dnanexus-integration". Create a safe upload plan for a FASTQ file with sample metadata.

Expected outcome:

A stepwise plan covering authentication, destination checks, metadata, upload, file closure, and post-upload verification.

Using "dnanexus-integration". Outline an applet that filters reads and returns a DNAnexus file.

Expected outcome:

An applet design covering input and output specifications, dependencies, processing steps, file links, error handling, and deployment checks.

Using "dnanexus-integration". Plan a parallel variant-calling workflow for multiple samples.

Expected outcome:

A monitored workflow plan with sample discovery, parallel jobs, output chaining, resource choices, retry rules, and final result collection.

Security Audit

Medium Risk

v9 • 7/23/2026 Open versioned report

All 45 static alerts are false positives caused by inert documentation, Markdown formatting, placeholders, and legitimate DNAnexus examples. No prompt injection or malicious data-exfiltration intent was found. Three medium-risk documentation issues remain concerning permissions, destructive cloud operations, and bearer token handling.

Files scanned

2,610

Lines analyzed

Review items

False positives ignored

Confirmed security concerns (3)

Medium

references/configuration.md:442-452

Overbroad DNAnexus Access Example

The configuration example combines unrestricted internet, project write, cross-project read, and developer access. Copying it can grant unnecessary privileges.

The permissions are explicitly combined in one copyable example. Each listed permission expands the app's authority beyond a minimal default.

Medium

references/data-operations.md:275-285 references/data-operations.md:319-330 references/job-execution.md:310-320

Sensitive Cloud Operations Lack Confirmation Guidance

The references show user invitations, permanent file deletion, and job termination without requiring target checks or explicit confirmation. Mistakes can alter access or lose work.

The cited examples directly perform privileged or destructive remote actions. No adjacent instruction requires impact review or user confirmation.

Medium

references/python-sdk.md:28-44

Bearer Token Placement in Examples

Authentication examples place token placeholders directly in Python and a shell export. Replacing them with real tokens can expose secrets through source or shell history.

The examples visibly assign a bearer token literal in code and a shell command. Placeholders reduce immediate exposure but encourage unsafe substitution.

Audited by: codex View Audit History →

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Academic citations (APA · BibTeX · CFF)

APA citation

davila7. (2026). dnanexus-integration security audit report (audit version 9) [Author version unspecified]. Skillstore. https://skillstore.io/skills/davila7-dnanexus-integration/audits/9

BibTeX citation

@techreport{davila7-davila7-dnanexus-integration-2026,
  author = {davila7},
  title = {dnanexus-integration security audit report (audit version 9)},
  institution = {Skillstore},
  year = {2026},
  number = {9},
  url = {https://skillstore.io/skills/davila7-dnanexus-integration/audits/9},
  note = {Author version unspecified}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "dnanexus-integration security audit report (audit version 9)"
version: "unspecified"
type: report
authors:
  - name: "davila7"
date-released: "2026-07-23"
url: "https://skillstore.io/skills/davila7-dnanexus-integration/audits/9"
identifiers:
  - type: other
    value: "skillstore:davila7-dnanexus-integration:audit:9"
    description: "Skillstore immutable audit report identifier"

Compare variants

2 installable variants

Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.

Why this variant is first

Highest Skillstore Score

Author / source Skillstore Score Evidence Confidence Skillstore usage Updated

K-Dense-AI Recommended

k-dense-ai-dnanexus-integration

Skillstore Score 71

Evidence Confidence High

Skillstore usage 8

Updated

2026-09-09

davila7 Current

davila7-dnanexus-integration

Skillstore Score 50

Evidence Confidence High

Skillstore usage 7

Updated

2026-09-09

Skillstore Score

Why this score Evidence Confidence: High

Architecture

Maintainability

Content

Community

Spec Compliance

What You Can Build

Develop a Genomics App

Create an applet structure, define inputs and outputs, add dependencies, and prepare deployment commands.

Automate Data Operations

Build a dxpy workflow to search, transfer, organize, and annotate sequencing files across projects.

Orchestrate Production Analyses

Design monitored, multi-stage DNAnexus jobs with output links, retries, resource settings, and failure handling.

Try These Prompts

Upload and Find Files

Show how to upload {local_file} to {project_id}, add {metadata}, and verify the uploaded DNAnexus file.

Create an Applet

Design a DNAnexus applet for {task} with {inputs}, {outputs}, required dependencies, and a safe testing procedure.

Build a Batch Pipeline

Create a dxpy pipeline that finds {file_pattern} in {project_id}, runs {applet_id} for each file, and monitors completion.

Design a Production Workflow

Plan a multi-stage DNAnexus workflow for {analysis}, including output links, permissions, instance types, retries, logging, and cost controls.

Best Practices

Use placeholders until project, file, applet, and region identifiers are confirmed.
Apply least-privilege access and confirm destructive or cost-bearing actions before execution.
Pin dependencies, test with representative data, and monitor job status, logs, outputs, and costs.

Avoid

Do not place API tokens in source files, prompts, command history, or shared logs.
Do not copy unrestricted network or cross-project permissions into every app.
Do not delete data, invite users, terminate jobs, or launch expensive workloads without explicit confirmation.

Frequently Asked Questions

Does this skill connect to DNAnexus automatically?

No. It provides guidance and examples; execution requires local tools, authentication, identifiers, permissions, and user-approved commands.

Which DNAnexus interfaces does it cover?

It covers the dx command line, the dxpy Python SDK, app and applet configuration, data objects, jobs, and workflows.

Can it handle FASTQ, BAM, and VCF workflows?

Yes. The patterns apply to common genomics files, but each tool, schema, resource setting, and validation rule requires project-specific adaptation.

Does it create or store credentials?

No. Use DNAnexus login or an approved secret manager, and never include real tokens in prompts or generated source files.

Can it manage production data?

It can guide production operations. Verify identifiers, permissions, retention requirements, and backups before modifying, moving, archiving, or deleting data.

How should cloud costs be controlled?

Review instance types, parallelism, storage classes, timeouts, retries, and expected data volume before launching jobs or workflows.