SKILLEMALL.ai

BC video-understand

Use when a video project needs reusable media metadata, word-level transcription, objective speech analysis, or evidence-backed semantic understanding before optional editing skills run.

ClawHub Agent Skills author: WhiteTowerAI v1.0.7 MIT-0 18 files · 12 scripts body ≈ 882 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

Use when a video project needs reusable media metadata, word-level transcription, objective speech analysis, or evidence-backed semantic understanding before…

As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

ProcedureMedia and videotype and topics are labelled automatically from the skill text
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
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: 16. 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 58/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 12 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 882 tokens

    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
    • -35 of 10 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 186: enough signal without eating the budget
    • +4Structure: 4 headings
    • +3Step-by-step instructions: 12 items
    • +4Has examples (5 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

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

    External checks

    ClawHub: suspicious
    The skill mainly describes video understanding, but it also ships under-disclosed editing and final-rendering code that can create output videos and update project state.
    LLM: suspicious (high) · 7 Oct 2026