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Skills brenda-database
📦
brenda-database
Content revision r1 Safe ⚡ Contains scripts⚙️ External commands🌐 Network access🔑 Env variables📁 Filesystem access
Analyze BRENDA enzyme data
Enzyme research often requires structured access to kinetic and organism-specific data. This skill helps Claude, Codex, and Claude Code query BRENDA records and turn them into usable biochemical analysis.
Supports: Claude Codex Code(CC)
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Agent request
Review the Skillstore skill "brenda-database" from https://skillstore.io/skills/k-dense-ai-brenda-database.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-brenda-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.
Test it
Using "brenda-database". Get Km values for alcohol dehydrogenase in yeast.
Expected outcome:
A concise table-style summary of substrates, Km values, organisms, units, references, and notes about incomplete records.
Using "brenda-database". Compare EC 1.1.1.1 across three organisms.
Expected outcome:
- Organism-by-organism kinetic comparison
- Most common substrates and cofactors
- Data gaps that need manual verification
Using "brenda-database". Create a pathway report for lactate production.
Expected outcome:
A readable pathway feasibility summary with enzyme candidates, reaction steps, condition constraints, and follow-up experiments.
Security Audit
Safev8 • 7/9/2026 Open versioned report
The audit found extensive static-analysis noise from Markdown formatting, EC numbers misread as IP addresses, and legitimate BRENDA credential setup. The only confirmed issue is that helper export functions write to caller-provided filenames, which can overwrite local files if used carelessly.
6
Files scanned
4,133
Lines analyzed
3
Review items
0
False positives ignored
Capability review items (3)
These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.
Medium
Python file write/append
with open(filename, 'w', newline='') as f:
The helper writes to a filename parameter without constraining the output path. This is intended export behavior, but a careless or model-chosen path could overwrite local files.
Medium
Python file write/append
with open(filename, 'w') as f:
The helper writes to a filename parameter without constraining the output path. This is intended export behavior, but a careless or model-chosen path could overwrite local files.
Medium
Python file write/append
with open(filename, 'w') as f:
The helper writes to a filename parameter without constraining the output path. This is intended export behavior, but a careless or model-chosen path could overwrite local files.
Risk Factors
⚡ Contains scripts (8)
⚙️ External commands (50)
evaluation_output.json:24 SKILL.md:35-46 SKILL.md:46-49 SKILL.md:49-53 SKILL.md:53-56 SKILL.md:56-67 SKILL.md:67-74 SKILL.md:74-85 SKILL.md:85-88 SKILL.md:88-99 SKILL.md:99-106 SKILL.md:106-116 SKILL.md:116-119 SKILL.md:119-124 SKILL.md:124-127 SKILL.md:127-132 SKILL.md:132-139 SKILL.md:139-150 SKILL.md:150-153 SKILL.md:153-158 SKILL.md:158-165 SKILL.md:165-174 SKILL.md:174-177 SKILL.md:177-185 SKILL.md:185-192 SKILL.md:192-203 SKILL.md:203-206 SKILL.md:206-214 SKILL.md:214-221 SKILL.md:221-231 SKILL.md:231-234 SKILL.md:234-243 SKILL.md:243-250 SKILL.md:250-259 SKILL.md:259-262 SKILL.md:262-267 SKILL.md:267-274 SKILL.md:274-285 SKILL.md:285-288 SKILL.md:288-293 SKILL.md:293-297 SKILL.md:297-299 SKILL.md:299-306 SKILL.md:306-309 SKILL.md:309-312 SKILL.md:312-315 SKILL.md:315-321 SKILL.md:321-332 SKILL.md:332-333 SKILL.md:333-334
🌐 Network access (50)
evaluation_output.json:36 evaluation_output.json:139 evaluation_output.json:159 evaluation_output.json:161 evaluation_output.json:187 references/api_reference.md:11 references/api_reference.md:78 references/api_reference.md:274 references/api_reference.md:293 references/api_reference.md:312 references/api_reference.md:318 references/api_reference.md:324 references/api_reference.md:352 references/api_reference.md:363 references/api_reference.md:380 references/api_reference.md:400 references/api_reference.md:413 references/api_reference.md:441 references/api_reference.md:453 scripts/brenda_queries.py:23 scripts/brenda_queries.py:827 scripts/brenda_queries.py:829 scripts/brenda_queries.py:837 scripts/brenda_queries.py:838 scripts/brenda_visualization.py:22 scripts/brenda_visualization.py:23 scripts/brenda_visualization.py:749 scripts/enzyme_pathway_builder.py:1032 SKILL.md:318 SKILL.md:713 SKILL.md:714 SKILL.md:715 SKILL.md:716 SKILL.md:717 SKILL.md:39 SKILL.md:42 SKILL.md:45 SKILL.md:78 SKILL.md:81 SKILL.md:84 SKILL.md:143 SKILL.md:156 SKILL.md:168 SKILL.md:180 SKILL.md:195 SKILL.md:209 SKILL.md:224 SKILL.md:237 SKILL.md:253 SKILL.md:265
🔑 Env variables (1)
📁 Filesystem access (3)
Audited by: claude View Audit History →
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APA citation
K-Dense-AI. (2026). brenda-database security audit report (audit version 8) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-brenda-database/audits/8BibTeX citation
@techreport{k-dense-ai-k-dense-ai-brenda-database-2026,
author = {K-Dense-AI},
title = {brenda-database security audit report (audit version 8)},
institution = {Skillstore},
year = {2026},
number = {8},
url = {https://skillstore.io/skills/k-dense-ai-brenda-database/audits/8},
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: "brenda-database security audit report (audit version 8)"
version: "unspecified"
type: report
authors:
- name: "K-Dense-AI"
date-released: "2026-07-09"
url: "https://skillstore.io/skills/k-dense-ai-brenda-database/audits/8"
identifiers:
- type: other
value: "skillstore:k-dense-ai-brenda-database:audit:8"
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
k-dense-ai-brenda-database
Skillstore Score 78
Evidence Confidence High
Skillstore usage 15
Updated
2026-09-09
davila7-brenda-database
Skillstore Score 70
Evidence Confidence High
Skillstore usage 8
Updated
2026-09-09
Skillstore Score
Why this score Evidence Confidence: High 64
Architecture
75
Maintainability
87
Content
71
Community
74
Spec Compliance
What You Can Build
Compare enzyme kinetics for a research project
Retrieve Km and kcat values for an EC number across organisms, substrates, and literature records.
Evaluate enzyme candidates for pathway design
Find enzymes, cofactors, inhibitors, activators, and environmental constraints for a target biochemical route.
Prepare teaching examples from curated enzyme data
Generate clear summaries and visualizations for enzyme classes, reactions, and kinetic behavior.
Try These Prompts
Look up basic enzyme kinetics
Use the BRENDA database skill to summarize Km and kcat data for EC 1.1.1.1. Include organisms, substrates, units, and important caveats.
Compare organisms for one enzyme
Compare alcohol dehydrogenase kinetic data across Saccharomyces cerevisiae, Escherichia coli, and Homo sapiens. Highlight substrate differences and missing data.
Assess operating conditions
Find pH, temperature, cofactor, inhibitor, and activator information for EC 1.1.1.1. Recommend conditions for a preliminary in vitro screen.
Build a pathway feasibility report
Use BRENDA data to outline an enzymatic pathway to lactate with up to three steps. Include candidate enzymes, organisms, cofactors, and feasibility risks.
Best Practices
- Use precise EC numbers and organism names to reduce ambiguous BRENDA matches.
- Store BRENDA credentials outside shared repositories and rotate them if exposed.
- Validate retrieved kinetic values against primary literature before using them in models.
Avoid
- Do not treat BRENDA output as experimental proof without expert review.
- Do not commit .env files or exported credential material to version control.
- Do not write exports into sensitive directories or overwrite existing research files.
Frequently Asked Questions
Does this skill require BRENDA credentials?
Yes. BRENDA requires a registered account, and the scripts expect credentials from environment variables or a local .env file.
Can it work without internet access?
No. Live queries require access to the BRENDA SOAP service unless you already have cached or exported data.
Can it analyze any enzyme?
It works best with valid EC numbers and records present in BRENDA. Missing or sparse records may limit the result.
Does it create visualizations?
Yes. The included visualization helpers can create plots for kinetic values, organism comparisons, pH, temperature, and substrate specificity.
Can it export results?
Yes. Helper functions can export selected kinetic and pathway data to local files such as CSV, JSON, Excel, or text reports.
Is the output ready for clinical or production decisions?
No. The output is research support material and should be reviewed by qualified domain experts before high-stakes use.
Developer Details
Author
K-Dense-AILicense
Unknown
Skillstore revision
r1
Version notice
The author did not declare a version.
Repository
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/brenda-databaseRef
3e4b6c31a74a3bd1a291c98cf585d720cb9fbc88
Maintenance freshness
7/18/2026
Usage
13 downloads · 244 views
File structure
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