SKILLEMALL.ai

AC k-factor-viral

Activate when: user says 'viral coefficient,' 'K-factor,' 'going viral,' 'our product is viral,' 'referral program,' 'invite mechanic,' 'built in sharing,' growth plateauing despite viral elements, or a growth forecast is being justified by virality without a K calculation. Do NOT activate when: product is B2B enterprise (sales-led growth); focus is engagement/retention not new-user acquisition; product has not yet achieved PMF. More: deciqai.com/c/k-factor-viral

ClawHub Agent Skills author: deciqAI v1.0.4 MIT-0 4 files body ≈ 1 552 tokens Open the sourceclawhub.ai analyzed 35 h ago

Activate when: user says 'viral coefficient,' 'K-factor,' 'going viral,' 'our product is viral,' 'referral program,' 'invite mechanic,' 'built in sharing,'…

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

ProcedureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
95
Run on models
none yet
Process rating
C
63/100
Has gaps
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: 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 63/100

    • 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. 3 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 26 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1552 tokens
    • low 10 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
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 467: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 26 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.

    External checks

    ClawHub: clean
    This is a text-only growth-analysis coaching skill with no executable behavior, data access, persistence, or hidden authority.
    LLM: benign (high) · VirusTotal: · 17 Jul 2026