SkillsBench is a benchmark for measuring how effectively AI agents use modular skills—folders containing instructions, scripts, and resources—to complete specialized tasks. It helps researchers and developers evaluate both skill quality and agent behavior, including tasks that require combining multiple skills. The catalogue’s skills and instructions are evaluated as part of this workflow.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add benchflow-ai/skillsbench --skill gttsgit clone --depth 1 https://github.com/benchflow-ai/skillsbenchWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/benchflow-ai/skillsbench/gtts)<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/gtts"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/gtts.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00052 | $0.00816 |
| Opus 5 | $0.00026 | $0.00408 |
| Sonnet 5 | $0.00010 | $0.00163 |
| Haiku 4.5 | $0.00005 | $0.00082 |
Grade A, and why
gtts scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- gtts — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Google Text-to-Speech (gTTS)
gTTS is a Python library that converts text to speech using Google's Text-to-Speech API. It's free to use and doesn't require an API key.
Installation
pip install gtts pydub
pydub is useful for manipulating and concatenating audio files.
Basic Usage
from gtts import gTTS
# Create speech
tts = gTTS(text="Hello, world!", lang='en')
# Save to file
tts.save("output.mp3")
Language Options
# US English (default)
tts = gTTS(text="Hello", lang='en')
# British English
tts = gTTS(text="Hello", lang='en', tld='co.uk')
# Slow speech
tts = gTTS(text="Hello", lang='en', slow=True)
Python Example for Long Text
from gtts import gTTS
from pydub import AudioSegment
import tempfile
import os
import re
def chunk_text(text, max_chars=4500):
"""Split text into chunks at sentence boundaries."""
sentences = re.split(r'(?<=[.!?])\s+', text)
chunks = []
current_chunk = ""
for sentence in sentences:
if len(current_chunk) + len(sentence) < max_chars:
current_chunk += sentence + " "
else:
if current_chunk:
chunks.append(current_chunk.strip())
current_chunk = sentence + " "
if current_chunk:
chunks.append(current_chunk.strip())
return chunks
def text_to_audiobook(text, output_path):
"""Convert long text to a single audio file."""
chunks = chunk_text(text)
audio_segments = []
for i, chunk in enumerate(chunks):
# Create temp file for this chunk
with tempfile.NamedTemporaryFile(suffix='.mp3', delete=False) as tmp:
tmp_path = tmp.name
# Generate speech
tts = gTTS(text=chunk, lang='en', slow=False)
tts.save(tmp_path)
# Load and append
segment = AudioSegment.from_mp3(tmp_path)
audio_segments.append(segment)
# Cleanup
os.unlink(tmp_path)
# Concatenate all segments
combined = audio_segments[0]
for segment in audio_segments[1:]:
combined += segment
# Export
combined.export(output_path, format="mp3")
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 136 lines · 52 tokens per session scan A d96a286fd3fa
gtts is a skill published in the GitHub repository benchflow-ai/skillsbench (1,754 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 52 tokens to every session and 816 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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