AB game-design-perceived-randomness-audit
Audit a game feature, combat system, loot table, reward loop, procedural system, chance mechanic, or uncertainty-driven design by how players are likely to perceive its randomness. Use when you need to evaluate whether a system will feel fair, streaky, rigged, sabotaging, manipulable, or skill-undermining; when players may misread independent events as patterned; or when randomness may sit too close to player action and create frustration. Analyze expectation gaps, gambler's-fallacy-style reactions, hidden pattern-seeking, input-versus-output randomness, perceived fairness, exploit risk, and ways to reshape presentation or mechanics.
As a process B 71/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, progress reporting
How to improve
- 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 71/100
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Inputs and preconditions. Does not say what the process needs to start
- 60Result and completion. Output format stated, no completion criterion
- 60Failures and branches. 2 branches
- 100Tools and files. No external tools needed
- 100Steps. 81 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1791 tokens
- 100Running it twice. Mutating operations check current state
- low 11 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)
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 641: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 81 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.