SKILLEMALL.ai

BD turbo-whisper-local-stt

当用户想要**音频转文字**、**语音转文本**、**转录录音**、**生成字幕**、**会议录音转文字**、**语音笔记转文本**、**本地转录音频**时自动触发。 使用本地 Faster-Whisper(large-v3-ct2 等模型)进行高性能、中文优先的音频转文字,完全离线、隐私安全,支持 wav/mp3/m4a 等格式和整个音频文件夹。 特别适合长音频(内置 VAD 分段)、会议/访谈/视频字幕等中文场景,输出结构化结果(完整文本 + 分段 + 时间戳)。 【重要约束】仅处理音频文件或音频文件夹,其他文件(如视频、图片、纯文本)一律不触发此技能。 常见触发口语(越多越好): - “帮我把这个音频转成文字” - “语音转文本 这个录音.mp3” - “转录这个会议录音” - “生成这个视频的字幕” (如果用户提供音频提取后的文件) - “本地转录音频 文件夹路径” - “把这个语音笔记转文字” - “音频转文字 会议.wav” - “帮我转录这段录音” - “语音识别 这个 m4a 文件” - “离线转文字” / “本地 STT”

ClawHub Agent Skills author: 顶尖王牌程序员 v1.0.8 MIT-0 9 files body ≈ 381 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
Run on models
none yet
Process rating
D
46/100
Unfinished process
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

  1. 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: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 46/100

  • 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
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 15 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 381 tokens
  • 100Running it twice. No mutating operations
  • low The response is described with custom markup (3 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

  • +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
  • -34 of 5 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 10 example trigger phrases
  • +3Description length 479: enough signal without eating the budget
  • +4Structure: 5 headings
  • +3Step-by-step instructions: 15 items

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

External checks

ClawHub: suspicious
This audio transcription skill is functional in purpose, but it automatically changes Python environments and may download packages and models despite strong offline/privacy claims.
LLM: suspicious (high) · 3 Jul 2026