AB personality-analyzer
Analyze a person's personality traits based on their written text or chat messages. Use this skill whenever the user wants to understand someone's personality, character, communication style, or behavioral tendencies from text. Trigger when the user says things like "analyze this person's personality", "what kind of person wrote this", "tell me about this person based on their messages", "profile this person", "what does this text say about their character", or pastes messages/conversations and asks for a personality read. Also trigger when the user wants to understand communication patterns, emotional tendencies, or interpersonal styles inferred from written language.
As a process B 69/100 · Nearly there — weak spots: inputs and preconditions, consistency, 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: 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 69/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 40Consistency. Frontmatter name (personality-analyzer) differs from the folder (personality-analysis-yang)
- 60Result and completion. Output format stated, no completion criterion
- 60Failures and branches. 2 branches
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 48 steps
- 100Execution cost. Instruction body is 1424 tokens
- 100Running it twice. No mutating operations
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
- +4Description does not say when NOT to use the skill (false activations)
- +1No license
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +3Description length 677: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 48 items
- +3Output format is stated explicitly
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.