SKILLEMALL.ai

AB lab-inventory-predictor

Predict depletion time of critical lab reagents based on historical usage frequency, and automatically generate purchase alerts when stock falls below safety thresholds.

ClawHub Agent Skills author: AIpoch v1.0.0 MIT-0 5 files body ≈ 2 066 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 75/100 · Nearly there — weak spots: running it twice

GeneratorInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
B
75/100
Nearly there
Running it twice w 4
30
When it triggers w 12
50
Tools and files w 18
60
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"
    • note frontmatter-key unknown frontmatter key "status"

    Process rating: all ten parameters 75/100

    • 30Running it twice. 1 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 43 steps
    • 100Failures and branches. 5 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2066 tokens
    • 100Progress reporting. Reports progress
    • low 13 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 169: enough signal without eating the budget
    • +4Structure: 24 headings
    • +3Step-by-step instructions: 43 items
    • +3Output format is stated explicitly
    • +4Has examples (6 code blocks)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: suspicious
    The skill appears to be a legitimate local lab-inventory tool, but its code does not enforce the workspace path limits that its documentation promises.
    LLM: suspicious (medium) · VirusTotal: · 29 May 2026