SKILLEMALL.ai
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ASR / STT / speech recognition / voice recognition engine powered by Volcengine LAS. Transcribes and converts speech to text from audio and video files — extracts spoken words and generates text transcription from any recording. Supports dictation, subtitle and caption generation. Handles meeting recordings, meeting notes, meeting minutes, meeting summary, interview transcription, podcast transcription, lecture transcription, customer service call center audio, phone call recording, and recorded audio files. Features speaker diarization and speaker identification (detect who said what), emotion recognition, sentiment detection, gender recognition, and multilingual multi-language auto-detection. Accepts wav, mp3, m4a formats with async submit-poll workflow and batch processing for large-scale transcription jobs. Use this skill when the user wants to transcribe audio or video to text (ASR/speech-to-text), generate subtitles or captions from recordings, do speaker diarization or emotion analysis on meeting/interview/podcast/lecture recordings, or extract spoken content from any audio/video media file.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: volcengine-skills v1.0.1 MIT-0 10 files · 4 scripts body ≈ 1 109 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ProcedureMedia and videotype 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
C
74/100
safety, quality, tests
Safety 60%
81
Quality 40%
63
Run on models
none yet
Process rating
C
61/100
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

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. Shorten the description to 1024 characters.
For the model run — optional
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 2

  • high Dangerous commands cmd-install-from-url scripts/env_init.sh:41
    Installs a package from an untrusted URL / archive
    pip install --quiet --upgrade https://las-ai-cn-beijing-online.tos-cn-beijing.volces.com/operator_cards_serving/public/skills/sdk/las_…whl
Medium and low: 1
  • low Dangerous commands cmd-background-process SKILL.md:122
    Starts a background / autostarted process
    ./scripts/poll_background.sh {task_id} "./output/{task_id}" & disown

Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-long description is 1115 chars, limit 1024

Process rating: all ten parameters 61/100

  • 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
  • 70When it triggers. States when to use, but not when not to
  • 100Tools and files. No external tools needed
  • 100Steps. 40 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1109 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress
  • medium 3 test cases, all positive: not one "should refuse" or "should ask first"

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 1115: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 40 items
  • +4Has examples (13 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +3All 4 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: suspicious
This is a legitimate speech-to-text skill, but its setup and background polling give it more local execution and persistence authority than users may expect.
LLM: suspicious (high) · VirusTotal: · 29 May 2026