SKILLEMALL.ai

AB listing-room-video-pack

Turn listing photos into a labeled set of listing room video clips, one room at a time. This listing video pack and real estate room video studio animates each listing photo into a short property video so buyers can preview the living room, bedroom, kitchen, and more as separate room clips. Use it for property room video, listing photo video, real estate listing video, and a labeled room video pack that keeps each space easy to scan. Add optional agent narration files beside the clips, or a talking-head intro and outro when you bring an agent portrait and a short script.

ClawHub Agent Skills author: beatra-ai v0.1.2 MIT-0 14 files body ≈ 2 274 tokens Open the sourceclawhub.ai analyzed 3 d ago

Turn listing photos into a labeled set of listing room video clips, one room at a time.

As a process B 71/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

ProcedureMedia and videotype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
B
71/100
Nearly there
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: 14. 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 71/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 4 mutating operations with no state check
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 15 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 3 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2274 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • 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)
    • +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
    • +3Description length 577: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 15 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (8 of 8)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: suspicious
    The skill is mostly transparent about being a remote Beatra media workflow, but its default silent self-updater and shared overbroad account token require Review before installation.
    LLM: suspicious (medium) · 6 Sept 2026