SKILLEMALL.ai

AB game-design-player-motivation-audit

Audit a game, feature, live-ops system, progression loop, social feature, or monetization surface using a Self-Determination Theory-inspired motivation framework. Use when evaluating what kind of motivation a design creates, comparing alternative motivational profiles, diagnosing why a system feels sticky, hollow, exhausting, or dead, checking overreliance on rewards and grind, or assessing whether a feature supports short-term activation, medium-term habit, or long-term player identity.

ClawHub Agent Skills author: Stanislav Stankovic v1.0.0 MIT-0 2 files body ≈ 2 918 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process B 65/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, running it twice

AnalyzerInfrastructurePersonal productivitytype 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
65/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 65/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 6 mutating operations with no state check
    • 55Failures and branches. 1 branches
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 164 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2918 tokens

    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)
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 492: enough signal without eating the budget
    • +4Structure: 34 headings
    • +3Step-by-step instructions: 164 items
    • +3Output format is stated explicitly

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

    External checks

    ClawHub: clean
    This is a text-only game design motivation audit guide with no code, install hooks, credentials, persistence, or hidden runtime behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026