SKILLEMALL.ai

AB founder-story-brand-narrative

Creates and refines Founder Story and brand narrative content for DTC/independent stores selling founder-driven products (e.g. handcrafted leather, artisan sauces, small-batch goods). Use whenever the user mentions founder story, brand story, about page, origin story, artisan brand, handcrafted brand, "who we are" copy, brand voice, mission/vision for a product brand, landing page hero narrative, PDP brand block, or wants to differentiate through authenticity and founder-led storytelling—even if they do not say "founder story" explicitly. Output structured narrative frameworks, placement guidance, and ready-to-use copy aligned with DTC best practices.

ClawHub Agent Skills author: RIJOY-AI v0.1.1 MIT-0 10 files body ≈ 2 692 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 72/100 · Nearly there — weak spots: inputs and preconditions, running it twice, progress reporting

GeneratorMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
99
Run on models
none yet
Process rating
B
72/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 9. 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 72/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Failures and branches. 4 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 63 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2692 tokens
    • medium 3 test cases, all positive: not one "should refuse" or "should ask first"

    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 2 example trigger phrases
    • +3Description length 659: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 63 items
    • +3Output format is stated explicitly
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 2 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 99.

    External checks

    ClawHub: clean
    The available evidence describes a writing-oriented skill with only routing and language-preference quality concerns, not hidden access or unsafe behavior.
    LLM: benign (medium) · VirusTotal: · 29 May 2026