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BC qiime2-amplicon

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.

K-Dense-AI/claude-scientific-skills Agent Skills author: K-Dense-AI MIT 3 files · 1 script body ≈ 1 949 tokens Open the sourcegithub.com↗ analyzed 12 h ago

Processes paired-end 16S amplicon reads into QIIME 2 ASVs and taxonomy with retained artifact provenance.

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

AnalyzerData and analyticsWriting and documentsSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
96
Quality 40%
80
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 4

✓ No critical or high findings

Medium and low: 4
  • low Secrets in code secret-high-entropy-token references/runtime-and-interpretation.md:45
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | `tools import` | `SampleData[PairedEndSequencesWithQuality]`, format `Pair…3V2`; `.qza` output. The underlying V2 manifest is QIIME metadata; this helper accepts a narrower li
    table
  • low Secrets in code secret-high-entropy-token scripts/amplicon_workflow.py:82
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    raise ValueError(f'Pair…3V2 requires tab-separated columns {fields}')
    quoted
  • low Secrets in code secret-high-entropy-token scripts/amplicon_workflow.py:195
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    '--input-format', 'Pair…3V2', '--input-path', args.manifest.resolve(),
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:45
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    Manifest is a **tab-separated** `Pair…3V2` file with exactly these headers:
    quoted

Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 51/100

  • 0Result and completion. Does not say what the result is
  • 0Failures and branches. Linear process with no failure handling
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 8 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1949 tokens
  • 100Progress reporting. Reports progress

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 308: enough signal without eating the budget
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 8 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.