BD video-pro
专业AI视频生成器 - 从文本到高质量短视频的完整解决方案，支持批量生成、多种模板和商业化功能
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
ProcedureMedia and videoInfrastructuretype and topics are labelled automatically from the skill text
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Plain value cannot start with reserved character @ at line 4, column 9: author: @cza999 ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 49/100
- 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
- 40Consistency. Frontmatter name (video-pro) differs from the folder (video-pro-cza)
- 100Tools and files. No external tools needed
- 100Steps. 74 steps
- 100Execution cost. Instruction body is 1330 tokens
- 100Running it twice. No mutating operations
- low 14 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)
- +3Description length 47: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -231 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 43 headings
- +3Step-by-step instructions: 74 items
- +4Has examples (14 code blocks)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.
External checks
ClawHub: suspicious
The skill appears intended for AI video generation, but it keeps sensitive scripts and license details in plaintext while making stronger privacy and licensing claims than the artifacts support.
LLM: suspicious (high) · VirusTotal: · 29 May 2026