SKILLEMALL.ai

AC shiguang-memory-journal

Turn video links/files into source-grounded, editable short-video posters and key frames/stories into memory journals. Use for 视频绘卷、短视频封面、电影感海报、海报标题或文字排版、参考海报风格迁移、关键帧重绘、可编辑手帐、对抗审稿,or 利用用户数据优化功能效果. Extract story evidence, compete visual and typography concepts, adapt reference structure without copying content, and audit factual fidelity, text integrity, thumbnail readability, and provenance. Do not use for generic image generation or verbatim poster copying.

ClawHub Agent Skills author: 李世荣 v2.6.0 MIT-0 16 files body ≈ 1 250 tokens Open the sourceclawhub.ai analyzed 2 d ago

Turn video links/files into source-grounded, editable short-video posters and key frames/stories into memory journals.

As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting

AnalyzerMedia and videoPersonal productivitytype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
62/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
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 62/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 100Tools and files. No external tools needed
    • 100Steps. 49 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1250 tokens
    • 100Running it twice. No mutating operations

    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
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 462: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 49 items
    • +4Reference files are cited in the instructions (8 of 8)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: clean
    This skill is a disclosed poster/journal workflow with privacy-bounded optimization and review steps, not hidden collection or unsafe execution.
    LLM: benign (high) · VirusTotal: · 3 Aug 2026