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BC jianying-auto-editor

Automate Jianying draft generation from local media plus a cloud editing API. Use when Codex needs to scan a material folder, request editing decisions, and write Jianying-oriented draft output for short-form video workflows.

ClawHub Agent Skills author: afengzi v0.1.1 MIT-0 8 files · 1 script body ≈ 301 tokens Open the sourceclawhub.ai↗ analyzed 8 d ago

Automate Jianying draft generation from local media plus a cloud editing API.

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorWriting and documentsMedia and videoSoftware developmenttype 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
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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: 8. 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 51/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 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. 1 mutating operations with no state check
    • 100Tools and files. No external tools needed
    • 100Steps. 39 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 301 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
    • +4No input/output examples
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 225: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 39 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

    External checks

    ClawHub: suspicious
    The skill matches its cloud video-editing purpose, but it has unsafe handling of credentials, local file metadata, and cloud-controlled output paths that users should review before installing.
    LLM: suspicious (high) · VirusTotal: · 12 Sept 2026