SKILLEMALL.ai

AB human-behavior-os

Diagnoses why specific users behave the way they do using a 7-module analytical framework (Needs, Attention, Trust, Decision, Emotion, Spread, Prediction). Outputs diagnostic analysis and behavioral insights ONLY — never generates persuasive copy, manipulation tactics, or growth-hacking instructions. Invoke ONLY when the user provides a specific scenario or case study and explicitly asks to DIAGNOSE, ANALYZE, or UNDERSTAND root causes of observed behavior patterns. Do NOT invoke for copywriting, campaign design, persuasion strategy, or any request to influence or change user behavior.

ClawHub Agent Skills author: Kelsey Hsiao v1.0.2 MIT-0 8 files body ≈ 4 112 tokens Open the sourceclawhub.ai analyzed 34 h ago

Diagnoses why specific users behave the way they do using a 7-module analytical framework (Needs, Attention, Trust, Decision, Emotion, Spread, Prediction).

As a process B 67/100 · Nearly there — weak spots: inputs and preconditions, failures and branches, running it twice

AnalyzerData and analyticsResearchWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
none yet
Process rating
B
67/100
Nearly there
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
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: 8. 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 67/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 4 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 70Execution cost. Instruction body is 4112 tokens
    • 100Tools and files. No external tools needed
    • 100Steps. 32 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place

    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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 591: enough signal without eating the budget
    • +4Structure: 49 headings
    • +3Step-by-step instructions: 32 items
    • +3Output format is stated explicitly
    • +4Has examples (12 code blocks)
    • +4Reference files are cited in the instructions (6 of 6)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: clean
    This skill is a text-only behavioral analysis framework with some marketing-adjacent diagnostic templates, but it does not install code, access data, execute actions, or hide its purpose.
    LLM: benign (high) · VirusTotal: · 11 Jun 2026