SKILLEMALL.ai

AB Hydration Habit Tuner

Build a simple daily water habit around the user's schedule using personalized cues, a bottle plan, and a 7-day check-in sheet.

ClawHub Agent Skills author: haidong v1.0.1 MIT-0 3 files body ≈ 2 604 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process B 73/100 · Nearly there — weak spots: result and completion, consistency, running it twice

GeneratorPersonal productivitytype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
B
73/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
    • note frontmatter-key unknown frontmatter key "type"
    • note frontmatter-key unknown frontmatter key "language"

    Process rating: all ten parameters 73/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 3 mutating operations with no state check
    • 40Consistency. Frontmatter name (Hydration Habit Tuner) differs from the folder (hydration-habit-tuner)
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 77 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 7 branches, has a failure section
    • 100Execution cost. Instruction body is 2604 tokens
    • low 10 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
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 127: enough signal without eating the budget
    • +4Structure: 22 headings
    • +3Step-by-step instructions: 77 items
    • +4Has examples (2 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: clean
    This is a prompt-only hydration routine planner with no code, network access, or credentials, though it may ask for personal schedule and health-constraint details.
    LLM: benign (medium) · VirusTotal: benign · 14 May 2026