SKILLEMALL.ai

AB protocol-deviation-classifier

Determine whether an incident in a clinical trial is a "major deviation.

ClawHub Agent Skills author: AIpoch v1.0.1 MIT-0 5 files body ≈ 3 619 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 76/100 · Nearly there — weak spots: consistency, running it twice

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
83
Run on models
none yet
Process rating
B
76/100
Nearly there
Running it twice w 4
30
Consistency w 8
40
When it triggers w 12
50
the three weakest of ten parameters · all ten

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-key unknown frontmatter key "skill-author"

    Process rating: all ten parameters 76/100

    • 30Running it twice. 1 mutating operations with no state check
    • 40Consistency. Frontmatter name (protocol-deviation-classifier) differs from the folder (protocol-deviation-classifier-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. 106 steps
    • 100Result and completion. Output format and completion criterion are stated
    • 100Failures and branches. 6 branches, has a failure section
    • 100Execution cost. Instruction body is 3619 tokens
    • 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)
    • +3Description length 72: 120–800 characters recommended
    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • +2Single-language instructions
    • +4Structure: 35 headings
    • +3Step-by-step instructions: 106 items
    • +3Output format is stated explicitly
    • +4Has examples (8 code blocks)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.

    External checks

    ClawHub: clean
    This is a local clinical-trial deviation classifier with no evidence of data theft or hidden system access, but its high-stakes recommendations should be reviewed by qualified staff.
    LLM: benign (high) · VirusTotal: · 29 May 2026