SKILLEMALL.ai

AB clinical-data-cleaner

Use when cleaning clinical trial data, preparing data for FDA/EMA submission, standardizing SDTM datasets, handling missing values in clinical studies, detecting outliers in lab results, or converting raw CRF data to CDISC format. Cleans and standardizes clinical trial data for regulatory compliance with audit trails.

ClawHub Agent Skills author: AIpoch v1.0.0 MIT-0 12 files body ≈ 2 282 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 79/100 · Nearly there — weak spots: consistency

AnalyzerData and analyticsInfrastructureSecuritytype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
94
Run on models
none yet
Process rating
B
79/100
Nearly there
Consistency w 8
40
When it triggers w 12
50
Tools and files w 18
60
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: ClawHub

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: 12. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "skill-author"

    Process rating: all ten parameters 79/100

    • 40Consistency. Frontmatter name (clinical-data-cleaner) differs from the folder (clinical-data-cleaner-1)
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 67 steps
    • 100Result and completion. Output format and completion criterion are stated
    • 100Failures and branches. 4 branches, has a failure section
    • 100Execution cost. Instruction body is 2282 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress
    • low 19 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 319: enough signal without eating the budget
    • +4Structure: 25 headings
    • +3Step-by-step instructions: 67 items
    • +3Output format is stated explicitly
    • +4Has examples (10 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 94.

    External checks

    ClawHub: clean
    This skill is a local clinical data cleaning tool whose file access and outputs fit its stated purpose, with dependency and validation cautions but no evidence of hidden or malicious behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026