BD analyze-video-by-qwen
|- 功能涵盖:。Use when 需要视频处理、音频编辑、媒体转换、配音生成时使用。不适用于版权受保护的媒体内容处理。适用于独立开发者、企业团队和自动化工作流场景。支持中文交互，无需复杂配置即开即用。输出结果可直接使用，减少二次加工成本。提供结构化输出和错误处理机制。支持多场景应用和灵活配置。具备完整的输入输出规范。 功能涵盖: analyze。
|- 功能涵盖:。Use when…
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
This is a copy of a skill from another catalog; the rating counts the canonical one: analyze-video-by-qwen (ClawHub)
How to improve
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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: 2. 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: Not a YAML token: 功能涵盖:。Use when 需要视频处理、音频编辑、媒体转换、配音生成时使用。不适用于版权受保护的媒体内容处理。适用于独立开发者、企业团队和自动化工作流场景。支持中文交互，无需复杂配置即开即用。输出结果可直接使用，减少二次加工成本。提供结构化输出和错误处理机制。支持多场景应用和灵活配置。具备完整的输入输出规范。 功能涵盖: analyze。 at line 9, column 17: description: |- 功能涵盖:。Use when 需要视频处理、音频编辑、媒体转换、配音生成时使用。不适用于版权受保护的媒体内容处理。适用于独立开… ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-long-hermesdescription is 175 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary" - note
frontmatter-keyunknown frontmatter key "summary_zh" - note
frontmatter-keyunknown frontmatter key "tools" - note
frontmatter-keyunknown frontmatter key "pricing_tier"
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 (analyze-video-by-qwen) differs from the folder (qwen-video-analyzer)
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 32 steps
- 100Execution cost. Instruction body is 1913 tokens
- 100Running it twice. No mutating operations
- low 13 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)
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +3Description length 175: enough signal without eating the budget
- +4Structure: 37 headings
- +3Step-by-step instructions: 32 items
- +4Has examples (12 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.
External checks
ClawHub: suspicious
This video-analysis skill has a coherent purpose, but its API-key handling, broad activation text, and third-party media transfer disclosure need review before installation.
LLM: suspicious (high) · 25 Aug 2026