SKILLEMALL.ai

AC live-commerce-script-studio

Turn a product lineup into a live shopping script your host can actually read on air. This live commerce script studio builds the run of show for the whole session as a minute-by-minute live selling schedule, writes a seven-step product demo talk track for every featured product, fills a library of ready-to-read lines for opening, holding, interacting, urgency, and closing, and runs a compliance pass over the wording — then renders the talking-point card and countdown card your host and floor manager work from, plus spoken takes of the lines that have to land on delivery. Reuse it as a live commerce script template session after session. Use it for livestream selling on Douyin, WeChat Channels, Taobao, Kuaishou, and Xiaohongshu, for brand-owned streams, creator collaborations, new-product sessions, clearance runs, and for getting a first-time live host through a session without freezing.

ClawHub Agent Skills author: beatra-ai v0.1.3 MIT-0 18 files body ≈ 2 588 tokens Open the sourceclawhub.ai analyzed 36 h ago

Turn a product lineup into a live shopping script your host can actually read on air.

As a process C 60/100 · Has gaps — weak spots: result and completion, running it twice, progress reporting

GeneratorSecurityMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
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
    • 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: 18. 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 60/100

    • 0Result and completion. Does not say what the result is
    • 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
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 21 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2588 tokens
    • low 10 top-level sections: this looks like several domains in one skill
    • low The skill ranks results itself: that belongs to the system behind the tool, not the model

    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)
    • +3Description length 900: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • -32 of 3 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 21 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (12 of 12)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: suspicious
    This skill is a legitimate live-commerce assistant, but it asks for broad account access and can silently replace its own installed code, so users should review it carefully before installing.
    LLM: suspicious (high) · 6 Sept 2026