AB western-blot-quantifier
Automatically identify Western Blot gel bands, perform densitometric analysis, and calculate normalized values relative to loading controls.
Automatically identify Western Blot gel bands, perform densitometric analysis, and calculate normalized values relative to loading controls.
As a process B 79/100 · Nearly there — weak spots: consistency
AnalyzerSoftware developmentData and analyticstype and topics are labelled automatically from the skill text
How to improve
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 · 0
✓ No critical or high findings
Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "skill-author"
Process rating: all ten parameters 79/100
- 40Consistency. Frontmatter name (western-blot-quantifier) differs from the folder (western-blot-quantifier-1)
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 72 steps
- 100Result and completion. Output format and completion criterion are stated
- 100Failures and branches. 1 branches, has a failure section
- 100Execution cost. Instruction body is 2710 tokens
- 100Running it twice. No mutating operations
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 26 top-level sections: this looks like several domains in one skill
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)
- +2Single-language instructions
- +3Description length 140: enough signal without eating the budget
- +4Structure: 35 headings
- +3Step-by-step instructions: 72 items
- +3Output format is stated explicitly
- +4Has examples (12 code blocks)
- +3All 2 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.
External checks
ClawHub: suspicious
This skill is not malware, but it materially overstates its Western blot analysis capability and installs broad unpinned dependencies, so users should review it carefully before use.
LLM: suspicious (high) · VirusTotal: · 16 Sept 2026