sag
ElevenLabs text-to-speech with mac-style say UX.
74
Does it follow best practices?
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npx tessl skill review --optimize ./path/to/skillEvaluation — 91%
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Validation for skill structure
Evaluation results
100%
73%Podcast Intro Generator Script
v3 audio tags and pause syntax
Uses sag CLI
0%
100%
v3 model or expressive default
0%
100%
Multiple distinct audio tags
0%
100%
Tags at line entrance
0%
100%
Correct v3 pause syntax
0%
100%
No SSML break tags
100%
100%
Voice selection
60%
100%
Output to file
60%
100%
Without context: $0.5331 · 2m 46s · 23 turns · 26 in / 9,329 out tokens
With context: $0.4747 · 1m 56s · 25 turns · 61 in / 6,023 out tokens
75%
22%Language Learning Audio Generator
Multi-language normalization and pronunciation
Uses sag CLI
0%
100%
Multilingual stable model
0%
100%
Language flag usage
100%
100%
Normalize flag applied
0%
100%
Normalize off for names
80%
100%
Respelling for pronunciation
100%
0%
Voice selection
0%
0%
Output files
100%
100%
API key via env var
100%
100%
Without context: $0.4768 · 2m 20s · 27 turns · 31 in / 7,623 out tokens
With context: $0.9550 · 3m 15s · 53 turns · 355 in / 10,484 out tokens
100%
100%AI Assistant Voice Response Feature
Chat voice response with character personas
Uses sag for audio
0%
100%
Output flag used
0%
100%
MEDIA: protocol in reply
0%
100%
Clawd voice used
0%
100%
Excited/scientist audio tags
0%
100%
Pauses in scientist voice
0%
100%
Whispers for calm voice
0%
100%
Sparse dramatic tags
0%
100%
Temp output path
0%
100%
Without context: $0.4744 · 2m 25s · 26 turns · 31 in / 7,321 out tokens
With context: $0.3883 · 1m 39s · 22 turns · 313 in / 4,957 out tokens
- Evaluated
- Agent
- Claude Code
- Model
- Unknown
Table of Contents
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