SKILLEMALL.ai

AB audio-to-text-and-video-to-text

Transcribe audio and video files into text using OpenAI's Whisper API. Use this skill whenever a user wants to convert any audio or video file to text — including MP3, MP4, WAV, M4A, OGG, WEBM, MOV, AVI, FLAC, and more. Trigger this skill for any request involving: "transcribe", "convert audio to text", "speech to text", "get transcript of", "extract audio from video", "meeting notes from recording", "subtitles", "captions", or similar. Also trigger when the user uploads or references a media file and asks what was said, discussed, or mentioned in it. If unsure whether audio/video transcription is involved, use this skill.

ClawHub Agent Skills author: Ahmad Hassam v1.0.0 MIT-0 5 files body ≈ 1 187 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 73/100 · Nearly there — weak spots: running it twice, progress reporting

IntegrationMedia and videotype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
none yet
Process rating
B
73/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
Tools and files w 18
60
the three weakest of ten parameters · all ten

How to improve

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

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 73/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 1 mutating operations with no state check
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 20 steps, 1 vague phrases
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1187 tokens
    • low 11 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

    • +4Description does not say when NOT to use the skill (false activations)
    • -4Absolute local paths (C:\Users, /home/…): not portable
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 8 example trigger phrases
    • +3Description length 630: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 20 items
    • +3Output format is stated explicitly
    • +4Has examples (5 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: clean
    This is a coherent transcription skill, but users should be careful because it sends media to OpenAI, handles an API key, and may install Python dependencies at runtime.
    LLM: benign (high) · VirusTotal: · 29 May 2026