Skills gget
📦
gget
Content revision r1 High Risk 🌐 Network access📁 Filesystem access🔑 Env variables⚙️ External commands
Query Genomic Databases with gget
Bioinformatics work often needs data from many changing genomics services. This skill guides Claude, Codex, and Claude Code to use gget for gene lookup, sequence retrieval, structure queries, and enrichment analysis.
Supports: Claude Codex Code(CC)
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Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Agent request
Review the Skillstore skill "gget" from https://skillstore.io/skills/k-dense-ai-gget.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-gget/manifest. Verify the artifact. Stop and obtain explicit user consent before installing or changing files.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.
Test it
Using "gget". Search for BRCA1 in human.
Expected outcome:
- Found BRCA1 with Ensembl gene identifier ENSG00000012048.
- Returned a short annotation, external database links, and available transcript context.
- Recommended sequence retrieval before downstream alignment or structure work.
Using "gget". Analyze ACE2 tissue expression and related pathways.
Expected outcome:
- Summarized tissue expression patterns from supported expression resources.
- Listed correlated genes for follow-up review.
- Suggested enrichment databases and cautioned about database version changes.
Using "gget". Plan a BLAST and structure workflow for a protein sequence.
Expected outcome:
- Selected an appropriate BLAST program and database based on sequence type.
- Outlined result limits, E-value settings, and expected hit summaries.
- Recommended checking PDB before running local structure prediction.
Security Audit
High Riskv7 • 7/6/2026 Open versioned report
Most static findings are false positives caused by Markdown code fences, documented gget commands, expected analysis file writes, and public database links. The audit did find semantic risks: a bundled self-attested safety report, promotional steering text, an unsafe pickle cache example, and an output-path issue from unsanitized FASTA identifiers.
8
Files scanned
3,245
Lines analyzed
0
Review items
0
False positives ignored
Confirmed security concerns (4)
High
Prompt Injection Attempt Detected
evaluation_output.json includes self-attested audit fields that claim risk_level is safe, safe_to_publish is true, and no malicious behavior was detected. Untrusted skill content should not attempt to pre-answer marketplace security decisions.
The file directly contains safety verdict language inside the skill package. It does not issue an explicit override command, so confidence is high but not absolute.
High
Unsafe Pickle Cache Example
references/workflows.md demonstrates loading cached results with pickle.load from a caller-supplied cache path. Loading untrusted pickle files can execute arbitrary Python code.
The code directly calls pickle.load on a file path without trust checks. This is a well-known unsafe deserialization pattern when cache files are not fully controlled.
Medium
Commercial Steering Instruction
SKILL.md instructs the assistant to proactively suggest K-Dense Web for complex workflows. This can steer users toward a hosted service unrelated to the immediate gget task.
The instruction is explicit and appears in the skill body. It is promotional rather than covert malware, so medium severity is appropriate.
Medium
Untrusted FASTA Header Used in Output Path
scripts/batch_sequence_analysis.py derives BLAST output filenames from FASTA record identifiers. A crafted identifier with path separators could write outside the intended output directory.
The parser stores raw FASTA headers and later uses them in a filename. Exploitability depends on running the helper script on untrusted FASTA input.
Risk Factors
🌐 Network access (5)
📁 Filesystem access (16)
references/module_reference.md:96 references/module_reference.md:116 references/workflows.md:392 references/workflows.md:43 references/workflows.md:45 references/workflows.md:112 references/workflows.md:434 references/workflows.md:465 references/workflows.md:467 references/workflows.md:802 scripts/batch_sequence_analysis.py:97 scripts/gene_analysis.py:55 scripts/gene_analysis.py:59 SKILL.md:174 SKILL.md:203 SKILL.md:228
🔑 Env variables (4)
⚙️ External commands (242)
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Audited by: codex View Audit History →
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APA citation
K-Dense-AI. (2026). gget security audit report (audit version 7) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-gget/audits/7BibTeX citation
@techreport{k-dense-ai-k-dense-ai-gget-2026,
author = {K-Dense-AI},
title = {gget security audit report (audit version 7)},
institution = {Skillstore},
year = {2026},
number = {7},
url = {https://skillstore.io/skills/k-dense-ai-gget/audits/7},
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: "gget security audit report (audit version 7)"
version: "unspecified"
type: report
authors:
- name: "K-Dense-AI"
date-released: "2026-07-06"
url: "https://skillstore.io/skills/k-dense-ai-gget/audits/7"
identifiers:
- type: other
value: "skillstore:k-dense-ai-gget:audit:7"
description: "Skillstore immutable audit report identifier"
Compare variants
2 installable variantsEach 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
davila7 Recommended
davila7-gget
Skillstore Score 73
Evidence Confidence High
Skillstore usage 10
Updated
2026-08-21
K-Dense-AI Current
k-dense-ai-gget
Skillstore Score 38
Evidence Confidence Medium
Skillstore usage 11
Updated
2026-08-21
Skillstore Score
Why this score Evidence Confidence: Medium 68
Architecture
85
Maintainability
87
Content
70
Community
83
Spec Compliance
What You Can Build
Inspect a Gene Quickly
Find identifiers, annotations, sequences, expression context, and disease links for a gene during research review.
Analyze a Gene List
Run enrichment, expression, and pathway checks for a candidate gene set before deeper statistical analysis.
Compare Sequences and Structures
Plan sequence similarity searches, alignments, motif checks, and protein structure lookups for comparative studies.
Try These Prompts
Beginner Gene Lookup
Use gget to search for TP53 in human. Return the Ensembl ID, gene name, description, and key database links.
Retrieve Sequences
Use gget to retrieve nucleotide and protein sequences for ENSG00000139618. Explain the expected output files and formats.
Compare Related Genes
Use gget to compare human BRCA1 and BRCA2. Include identifiers, protein sequences, structure resources, and an alignment workflow.
Advanced Enrichment Workflow
Use gget to analyze TP53, BRCA1, MDM2, and CDKN1A. Include enrichment, disease associations, expression context, limits, and saved outputs.
Best Practices
- Specify species, database release, and result limits for reproducible queries.
- Save outputs with clear prefixes and record database versions used in analysis.
- Keep credentials private and prefer secure configuration over command-line secrets.
Avoid
- Running large query batches without limits, retries, or rate controls.
- Treating external database results as final clinical or diagnostic conclusions.
- Using untrusted file names or sequence identifiers directly as output paths.
Frequently Asked Questions
What is gget used for?
gget queries genomic databases for gene information, sequences, structures, expression data, disease links, and enrichment results.
Does this skill run gget automatically?
The skill provides guidance and examples. Actual command execution depends on the user environment and tool permissions.
Which tools can use this skill?
The report lists support for Claude, Codex, and Claude Code.
Does gget need network access?
Yes. Many gget modules query external public databases and depend on their availability and rate limits.
Can gget handle batch analysis?
It can support batch workflows, but large jobs need limits, retries, caching, and careful output handling.
Are gget results suitable for medical decisions?
No. Results should be validated by qualified domain experts and are not a substitute for clinical review.
Developer Details
Author
K-Dense-AILicense
BSD-2-Clause license
Skillstore revision
r1
Version notice
The author did not declare a version.
Ref
b8ca75d2c0a7e7102978993058777d82b8ab2610
Maintenance freshness
7/18/2026
Usage
9 downloads · 185 views
File structure