SKILLEMALL.ai

AC smart-surprise

A proactive AI companion that initiates casual conversations with users at unpredictable times, making the AI feel like a real partner rather than a passive tool. Use when you want to bring surprise, warmth, and variety to user interactions — sending greetings, sharing tips, checking in on wellbeing, or sparking interesting conversations based on the user's personal preferences. Activate when: (1) a user installs this skill and triggers the initial cron, (2) you want to proactively reach out to a user instead of always waiting to be messaged first. This skill manages a self-perpetuating chain of one-shot cron jobs — each run delivers a personalized message, learns from user preferences, schedules the next random trigger, then deletes itself.

ClawHub Agent Skills author: TuringCorp.net v1.1.0 MIT-0 7 files body ≈ 1 974 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 63/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
C
63/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
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: 7. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: A proactive AI companion that initiates casual conversations with … ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value

    Process rating: all ten parameters 63/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 8 mutating operations with no state check
    • 65Failures and branches. 3 branches
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 47 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1974 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 751: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 47 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

    External checks

    ClawHub: suspicious
    This skill is not clearly malicious, but it creates an always-running surprise messenger that can contact users, learn preferences silently, and optionally use calendar credentials.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026