audio-transcriber
Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration
Install with Tessl CLI
npx tessl i github:sickn33/antigravity-awesome-skills --skill audio-transcriber50
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillEvaluation — 85%
↑ 2.17xAgent success when using this skill
Validation for skill structure
Evaluation results
86%
56%Podcast Transcription Automation Script
Faster-Whisper model parameters and output file naming
Faster-Whisper import
0%
100%
Whisper fallback
0%
100%
CPU device param
0%
100%
int8 compute type
0%
100%
VAD filter enabled
0%
100%
Word timestamps enabled
0%
100%
Default model is base
100%
100%
Timestamp output naming
0%
0%
Segment timestamps in output
40%
80%
No hardcoded API keys
100%
100%
Language auto-detect
100%
100%
Without context: $0.3964 · 6m 38s · 23 turns · 70 in / 5,180 out tokens
With context: $1.1191 · 6m 50s · 35 turns · 7,047 in / 10,895 out tokens
86%
49%Meeting Documentation from Raw Transcript Data
Markdown report template structure
Top-level title
0%
100%
Metadata section heading
50%
100%
Metadata as table
100%
100%
All metadata fields present
100%
100%
Meeting minutes heading
100%
100%
Participants subsection
25%
100%
Topics subsection
25%
100%
Decisions with checkmark prefix
0%
0%
Action items with checkboxes
0%
100%
Segment timestamps MM:SS format
0%
71%
No large prose dump
100%
100%
Footer attribution
0%
100%
Without context: $0.1831 · 2m 12s · 11 turns · 15 in / 2,778 out tokens
With context: $0.5972 · 4m 29s · 18 turns · 7,030 in / 6,577 out tokens
85%
33%Universal Audio Meeting Summarizer Tool
Auto-detection, LLM CLI integration, and RISEN prompt
Claude CLI first
100%
100%
GH Copilot fallback
100%
100%
Claude invoked via stdin
0%
100%
RISEN prompt structure
0%
41%
RISEN documents in design notes
0%
0%
Rich library for UI
100%
100%
Temp file cleanup
100%
100%
Faster-whisper preferred
0%
100%
Detection order documented
100%
100%
No hardcoded API keys
100%
100%
Timestamp file naming
0%
100%
Without context: $0.5421 · 6m 50s · 24 turns · 31 in / 9,163 out tokens
With context: $0.7600 · 5m 10s · 23 turns · 3,196 in / 9,308 out tokens
- Evaluated
- Agent
- Claude Code
- Model
- Unknown
Table of Contents
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