qiime2-amplicon
1 finding (1 high), mainly resource abuse. Most recent scan 2026-10-21.
Second scanner: NVIDIA SkillSpector
Independent static run, no language model, over the same files as the Cisco scan above. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Processes paired-end 16S amplicon reads into QIIME 2 ASVs and taxonomy with retained artifact provenance. Checks paired FASTQ manifests, primer orientation diagnostics, predicted post-trimming overlap, sample IDs, runtime versions and read retention, and guides selection of compatible taxonomic classifiers.
- Package
- 3 files, 37 KB
- SKILL.md
- 935 words, 6 sections
- Code
- Python (1)
- License
- MIT
- Compatibility
- Python 3.10+ for the standard-library validation helper; QIIME 2 2026.7 distribution with cutadapt, dada2, demux, feature-table, feature-classifier, taxa and types plugins for execution. Install through the official conda/container distribution, not PyPI. Requires a compatible trusted classifier and network for installation/reference downloads.
SKILL.md covers: QIIME 2 paired-end 16S amplicons · Establish the assay before running · Input files · Execute · Inspect results before analysis · Primary references
Findings
HIGH Infinite loop without clear exit condition Resource Abusestatic
Pattern detected: while True:
scripts/amplicon_workflow.py:28
while True:What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 8.4 KB |
references/runtime-and-interpretation.md | doc | 13 KB |
scripts/amplicon_workflow.py | script | 15 KB |
External hosts referenced
github.com amplicon-docs.qiime2.org library.qiime2.org cutadapt.readthedocs.io use.qiime2.org view.qiime2.org
Hostnames that appear in the skill's files. Referencing a host is not a finding; compare against the findings above and the skill's stated purpose.
Package contents recorded 2026-10-22 at commit 593377bb0487. The scan above ran against the version current at scan time; the two can differ if the skill has since been updated.
What we checked
- Static analyzer. Pattern rules over SKILL.md and bundled files: known-bad commands, exfiltration URLs, secrets, obfuscation.
- Bytecode analyzer.
- Pipeline analyzer.
- Correlation analyzer.
- Behavioral analyzer. Checks what the skill asks the agent to do against what its description claims it does.
- Trigger analyzer. Looks for instructions that fire on conditions the user did not ask for.
What we did not check
- Runtime behaviour. The skill was not executed; findings come from reading its files.
- Anything fetched at install or run time, including remote scripts, package dependencies, and URLs the skill tells the agent to open.
- Content the analyzers cannot read: images, binaries, and some non-English text.
- Known scanner bypass classes. See the methodology and limitations page.
Sources
- Repository: https://github.com/K-Dense-AI/scientific-agent-skills
- Raw scan result: skills-qiime2-amplicon-scan.json
- Badge for your README:
- Request a re-scan