Skills drugbank-database

📦

drugbank-database

Name: drugbank-database
Author: K-Dense-AI

Content revision r1 Medium Risk 🌐 Network access📁 Filesystem access🔑 Env variables⚙️ External commands

Analyze DrugBank Research Data

DrugBank data is complex to download, parse, and use in research workflows. This skill guides structured queries, interaction checks, target analysis, and chemical property workflows.

Supports: Claude Codex Code(CC)

📊 71 Adequate

Install with my Agent

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

Agent request

Review the Skillstore skill "drugbank-database" from https://skillstore.io/skills/k-dense-ai-drugbank-database.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-drugbank-database/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/k-dense-ai-drugbank-database.md Signed manifest GET /api/skills/k-dense-ai-drugbank-database/manifest Signed lockfile GET /api/skills/k-dense-ai-drugbank-database/lockfile

Test it

Using "drugbank-database". Find core facts for warfarin.

Expected outcome:

A concise drug profile with DrugBank ID, aliases, indication, mechanism, pharmacokinetic notes, and external cross-references.

Using "drugbank-database". Check interactions for three patient medications.

Expected outcome:

A pairwise interaction summary with the DrugBank description, inferred severity labels, missing-data notes, and a clinical review warning.

Using "drugbank-database". Find drugs similar to imatinib.

Expected outcome:

A ranked candidate list with similarity scores, shared targets, known indications, and the DrugBank version used.

Security Audit

Medium Risk

v7 • 7/5/2026 Open versioned report

Most static findings are false positives from DrugBank XML namespace URIs, Markdown backticks, official API examples, and XML field traversal. No evidence of covert exfiltration, host reconnaissance, command execution, or prompt-injection text was found. Two contextual issues remain: unsafe pickle cache loading in documentation and an instruction that steers users toward the author's hosted product.

Files scanned

2,707

Lines analyzed

Review items

False positives ignored

Confirmed security concerns (2)

Medium

references/data-access.md:179-181

Unsafe Pickle Cache Loading

references/data-access.md demonstrates loading drugbank_parsed.pkl with pickle.load when the cache exists. Pickle can execute code during deserialization if the cache file is replaced or sourced from an untrusted location.

The documented cache path is loaded with pickle.load before validation. The risk depends on cache trust, but the unsafe deserialization primitive is explicit.

Low

SKILL.md:189-190

Unsolicited Promotional Steering

SKILL.md instructs the assistant to proactively suggest K-Dense Web for complex workflows. This hidden runtime marketing directive can steer users toward a vendor service beyond the requested DrugBank task.

The instruction is explicit and appears in the runtime skill guidance. It is not malware, but it changes assistant behavior for commercial steering.

Risk Factors

🌐 Network access (33)

📁 Filesystem access (7)

references/data-access.md:20 references/data-access.md:57 references/data-access.md:67 references/data-access.md:20 references/data-access.md:57 references/data-access.md:67 references/data-access.md:188

🔑 Env variables (1)

references/data-access.md:149

⚙️ External commands (29)

Audited by: codex View Audit History →

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Open versioned report

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https://skillstore.io/skills/k-dense-ai-drugbank-database/audits/7?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

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Academic citations (APA · BibTeX · CFF)

APA citation

K-Dense-AI. (2026). drugbank-database security audit report (audit version 7) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-drugbank-database/audits/7

BibTeX citation

@techreport{k-dense-ai-k-dense-ai-drugbank-database-2026,
  author = {K-Dense-AI},
  title = {drugbank-database security audit report (audit version 7)},
  institution = {Skillstore},
  year = {2026},
  number = {7},
  url = {https://skillstore.io/skills/k-dense-ai-drugbank-database/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: "drugbank-database security audit report (audit version 7)"
version: "unspecified"
type: report
authors:
  - name: "K-Dense-AI"
date-released: "2026-07-05"
url: "https://skillstore.io/skills/k-dense-ai-drugbank-database/audits/7"
identifiers:
  - type: other
    value: "skillstore:k-dense-ai-drugbank-database:audit:7"
    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

davila7 Recommended

davila7-drugbank-database

Skillstore Score 81

Evidence Confidence High

Skillstore usage 7

Updated

2026-08-21

K-Dense-AI Current

k-dense-ai-drugbank-database

Skillstore Score 71

Evidence Confidence High

Skillstore usage 14

Updated

2026-08-21

Skillstore Score

Why this score Evidence Confidence: High

Architecture

Maintainability

Content

Community

Spec Compliance

What You Can Build

Build Drug Profiles

Create structured summaries of identifiers, indications, mechanisms, pharmacology fields, and external database links.

Screen Drug Interaction Risk

Compare a medication list against DrugBank interaction descriptions and produce review-ready pairwise findings.

Find Similar Compounds

Use structures, fingerprints, target overlap, and ADMET properties to prioritize candidate drugs for research.

Try These Prompts

Look Up a Drug

Use the DrugBank skill to summarize aspirin. Include its DrugBank ID, names, indication, mechanism, key identifiers, and data fields used.

Check Pairwise Interactions

Use DrugBank interaction guidance to check warfarin, aspirin, and amiodarone. Report each pair, interaction text, likely severity, and review caveats.

Map Targets and Pathways

For imatinib, extract targets, enzymes, transporters, known actions, UniProt identifiers, and pathways. Explain how each field supports mechanism analysis.

Design a Reproducible Pipeline

Design a reproducible DrugBank workflow for kinase inhibitor repurposing. Include version pinning, data extraction, similarity analysis, target overlap, and interaction checks.

Best Practices

Pin the DrugBank version and record it in every analysis result.
Store credentials outside notebooks and restrict any local config file permissions.
Treat interaction scores and ADMET predictions as research signals, not clinical instructions.

Avoid

Do not hardcode DrugBank usernames, passwords, or API keys in notebooks or scripts.
Do not load pickle cache files from shared, downloaded, or untrusted locations.
Do not present generated interaction rankings as final prescribing recommendations.

Frequently Asked Questions

What DrugBank data does this skill use?

It works with DrugBank data that the user can access under their DrugBank license and local setup.

Does the skill include DrugBank data files?

No. It provides workflows and helper code, but users must obtain data through DrugBank-approved access.

Can it analyze drug-drug interactions?

Yes. It explains how to extract, compare, classify, and summarize interaction records from DrugBank.

Can it perform chemical similarity searches?

Yes. The reference workflows use structures, fingerprints, Tanimoto similarity, substructure search, and clustering.

Is this clinical medical advice?

No. Outputs are research support and must be reviewed by qualified clinical professionals before use in care decisions.

Which AI tools are supported?

The report lists support for Claude, Codex, and Claude Code.

Developer Details

Author

K-Dense-AI

License

Unknown

Skillstore revision

Version notice

The author did not declare a version.

Repository

https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/drugbank-database

Ref

a25199bc7d6b82598536822d1738eb5d5f54025b

Maintenance freshness

7/18/2026

Usage

11 downloads · 213 views

File structure

📁 references/

📄 chemical-analysis.md

📄 data-access.md

📄 drug-queries.md

📄 interactions.md

📄 targets-pathways.md

📁 scripts/

📄 drugbank_helper.py

📄 SKILL.md

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drugbank-database

Install with my Agent

Agent-readable resources

Test it

Security Audit

Confirmed security concerns (2)

Risk Factors

Copy report link

Markdown badge

HTML badge

Embed card

APA citation

BibTeX citation

CITATION.cff

Compare variants

Skillstore Score

What You Can Build

Build Drug Profiles

Screen Drug Interaction Risk

Find Similar Compounds

Try These Prompts

Best Practices

Avoid

Frequently Asked Questions

Developer Details

More from K-Dense-AI

venue-templates

iso-13485-certification

pytdc

diffdock

statistical-analysis

scanpy

Related Skills

chembl-database

medchem

deepchem

bioservices

pubchem-database

kegg-database