BC azure-ai-voicelive-py
纯文档型Azure语音SDK技能,麦克风/转写/凭据说明。〉 **核心功能**: 本技能提供、格式互转、内容提取时使用、化工作流场景等能力。。适用于多种工作场景,提供专业的能力支持。支持多种输入格式,输出结构化结果,适配独立开发者与小型团队。提供专业能力支持,覆盖多场景工作流,支持自动化处理。Use when 需要代码生成、编程辅助、调试测试、开发部署时使用。不适用于无明确技术栈的模糊需求。
纯文档型Azure语音SDK技能,麦克风/转写/凭据说明。〉 核心功能: 本技能提供、格式互转、内容提取时使用、化工作流场景等能力。。适用于多种工作场景,提供专业的能力支持。支持多种输入格式,输出结构化结果,适配独立开发者与小型团队。提供专业能力支持,覆盖多场景工作流,支持自动化处理。Use when…
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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: Nested mappings are not allowed in compact mappings at line 6, column 14: description: 纯文档型Azure语音SDK技能,麦克风/转写/凭据说明。〉 **核心功能**: 本技能提供、格式互转、内容提取时使用、化工作流场景… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-long-hermesdescription is 197 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 "tools" - note
frontmatter-keyunknown frontmatter key "pricing_tier"
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
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 6 mutating operations with no state check
- 40Consistency. Frontmatter name (azure-ai-voicelive-py) differs from the folder (azure-voicelive-2)
- 50Failures and branches. 0 branches, has a failure section
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 75 steps
- 100Execution cost. Instruction body is 3077 tokens
- low 29 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 197: enough signal without eating the budget
- +4Structure: 58 headings
- +3Step-by-step instructions: 75 items
- +4Has examples (15 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.