Local text-to-speech via sherpa-onnx (offline, no cloud)
70
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 — 100%
↑ 1.51xAgent success when using this skill
Validation for skill structure
CLI wrapper usage and env var configuration
SHERPA_ONNX_RUNTIME_DIR usage
0%
100%
SHERPA_ONNX_MODEL_DIR usage
0%
100%
Output flag -o
0%
100%
Correct command name
100%
100%
Sequential naming
100%
100%
Blank line skipping
100%
100%
Output subdirectory
100%
100%
No hardcoded paths
100%
100%
README env configuration
0%
100%
PATH or baseDir invocation
0%
100%
Without context: $0.2910 · 1m 8s · 20 turns · 27 in / 3,663 out tokens
With context: $0.5192 · 1m 38s · 28 turns · 32 in / 5,761 out tokens
Multi-model configuration and openclaw.json setup
openclaw.json path
100%
100%
skills.entries key
20%
100%
SHERPA_ONNX_RUNTIME_DIR in config
0%
100%
SHERPA_ONNX_MODEL_DIR in config
25%
100%
Runtime install path
100%
100%
Models install path
100%
100%
Model file flag
100%
100%
Tokens file override
66%
100%
Output flag usage
60%
100%
Voice-parameterized path
100%
100%
Without context: $0.3057 · 1m 19s · 16 turns · 21 in / 5,087 out tokens
With context: $0.5384 · 2m 2s · 22 turns · 27 in / 7,498 out tokens
Cross-platform binary invocation and library path setup
Correct binary name
0%
100%
Binary in bin/ subdir
100%
100%
.exe on Windows
50%
100%
LD_LIBRARY_PATH on Linux
100%
100%
DYLD_LIBRARY_PATH on macOS
100%
100%
PATH extension on Windows
100%
100%
lib/ directory used
100%
100%
--vits-model flag
100%
100%
--vits-tokens flag
100%
100%
--vits-data-dir flag
100%
100%
--output-filename flag
100%
100%
Without context: $0.2510 · 1m 15s · 14 turns · 20 in / 4,975 out tokens
With context: $0.4879 · 1m 41s · 22 turns · 27 in / 6,381 out tokens
Table of Contents
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