SKILLEMALL.ai

AB game-design-zeigarnik-effect-audit

Audit a game, feature, task system, quest flow, event track, puzzle chain, progression layer, or return loop through the lens of the Zeigarnik effect: the tension created by incomplete, interrupted, or unresolved tasks. Use when evaluating whether a design creates healthy return motivation through open loops, whether it leaves players with productive unfinished business, or whether it turns incompletion into anxiety, clutter, guilt, or manipulative pressure.

ClawHub Agent Skills author: Stanislav Stankovic v1.0.0 MIT-0 4 files body ≈ 1 787 tokens Open the sourceclawhub.ai analyzed 3 d ago

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

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
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: 4. 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. 10 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. 112 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1787 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 462: enough signal without eating the budget
    • +4Structure: 25 headings
    • +3Step-by-step instructions: 112 items
    • +3Output format is stated explicitly
    • +4Reference files are cited in the instructions (2 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This is an instruction-only game-design audit skill that does not install code, access credentials, use the network, or modify user data.
    LLM: benign (high) · VirusTotal: · 29 May 2026