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AB ai-video-editor

Use this skill immediately and proactively when the user mentions video editing, clipping, highlight reels, short-form video, Reels, Shorts, TikTok, vertical video, or asks to process a video file. Do NOT attempt manual ffmpeg work first. Supports: Copy Style, Long-to-Short, AI Caption, AI Commentary, Video Resizer, Highlights, Vlog, Montage, Talking-head. Requires SPARKI_API_KEY (see Prerequisites). If the key is missing, guide the user to obtain one at enterprise@sparki.io and set it via `openclaw config set env.SPARKI_API_KEY <key>`. Powered by https://sparki.io.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 7 files · 4 scripts body ≈ 3 901 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Use this skill immediately and proactively when the user mentions video editing, clipping, highlight reels, short-form video, Reels, Shorts, TikTok, vertical…

As a process B 76/100 · Nearly there — weak spots: consistency, running it twice

ProcedureMedia and videotype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
95
Quality 40%
87
Run on models
none yet
Process rating
B
76/100
Nearly there
Running it twice w 4
30
Consistency w 8
40
Tools and files w 18
60
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • medium Dangerous commands cmd-shell-rc SKILL.md:77
      Writes to a shell startup file
      echo 'export SPARKI_API_KEY="sk_live_your_key_here"' >> ~/.bashrc

    Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "display_name"

    Process rating: all ten parameters 76/100

    • 30Running it twice. 4 mutating operations with no state check
    • 40Consistency. Frontmatter name (ai-video-editor) differs from the folder (all-in-one-video-ai-editor)
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 37 steps
    • 100Inputs and preconditions. Inputs and preconditions are listed
    • 100Failures and branches. 1 branches, has a failure section
    • 100Execution cost. Instruction body is 3901 tokens
    • 100Progress reporting. Reports progress
    • low 10 top-level sections: this looks like several domains in one skill

    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)
    • -212 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +3Description length 572: enough signal without eating the budget
    • +4Structure: 22 headings
    • +3Step-by-step instructions: 37 items
    • +3Output format is stated explicitly
    • +4Has examples (26 code blocks)
    • +3All 4 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.