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BC best-youtube-video-editor

The best-youtube-video-editor skill on ClawHub transforms how YouTube creators produce content by enabling conversational, AI-driven video editing without timelines or complex software. Trim dead air, add chapter markers, layer captions, adjust pacing, and optimize exports — all through plain-language instructions. On first use, the skill auto-configures credentials via NemoVideo API, so you're editing within seconds of activation. Built for YouTubers, educators, podcasters, and brand channels who need fast turnaround without sacrificing quality. Supports mp4, mov, avi, webm, and mkv formats.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 2 files body ≈ 5 243 tokens Open the sourcegithub.com↗ analyzed 2 d ago

The best-youtube-video-editor skill on ClawHub transforms how YouTube creators produce content by enabling conversational, AI-driven video editing without…

As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorYouTubeMedia 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
B
85/100
safety, quality, tests
Safety 60%
95
Quality 40%
71
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Exfiltration net-credential-use SKILL.md:91
    Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
    $API = `${NEMO_API_URL:-https://mega-api-prod.nemovideo.ai}`, $TOKEN = `${NEMO_TOKEN}`, $WEB = `${NEMO_WEB_URL:-https://nemovideo.com}`.
    vendor-host
  • low Exfiltration net-credential-use SKILL.md:153
    Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host; quoted — discussed, not commanded)
    **File upload**: `curl -s -X POST "https://mega-api-prod.nemovideo.ai/api/upload-video/nemo_agent/me/<sid>" -H "Authorization: Bearer $TOKEN" -H "X-Skill-Source: $SKILL_NAME" -H "X-Skill-Version: $SKI
    vendor-hostquoted
  • low Exfiltration net-credential-use SKILL.md:155
    Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host; quoted — discussed, not commanded)
    **URL upload**: `curl -s -X POST "https://mega-api-prod.nemovideo.ai/api/upload-video/nemo_agent/me/<sid>" -H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" -H "X-Skill-Source: $SK
    vendor-hostquoted
  • low Exfiltration net-credential-use SKILL.md:165
    Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
    curl -s "https://mega-api-prod.nemovideo.ai/api/credits/balance/simple" -H "Authorization: Bearer $TOKEN" \
    vendor-host
  • low Exfiltration net-credential-use SKILL.md:173
    Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
    curl -s "https://mega-api-prod.nemovideo.ai/api/state/nemo_agent/me/<sid>/latest" -H "Authorization: Bearer $TOKEN" \
    vendor-host

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5243 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "apiDomain"
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "repository"

Process rating: all ten parameters 55/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 21 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 70Execution cost. Instruction body is 5243 tokens
  • 100Steps. 31 steps
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 10 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (5 tags): a typed call is more reliable

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
  • +1No license
  • +2Single-language instructions
  • +3Description length 599: enough signal without eating the budget
  • +4Structure: 22 headings
  • +3Step-by-step instructions: 31 items
  • +4Has examples (8 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.