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 python-scala-oopgit 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/python-scala-oop)<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/python-scala-oop"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/python-scala-oop/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/python-scala-oop"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/python-scala-oop.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00049 | $0.02040 |
| Opus 5 | $0.00024 | $0.01020 |
| Sonnet 5 | $0.00010 | $0.00408 |
| Haiku 4.5 | $0.00005 | $0.00204 |
Grade A, and why
python-scala-oop 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 9d 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:
- python-scala-oop — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 377 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python to Scala OOP Translation
Basic Classes
# Python
class Person:
def __init__(self, name: str, age: int):
self.name = name
self.age = age
def greet(self) -> str:
return f"Hello, I'm {self.name}"
// Scala
class Person(val name: String, val age: Int) {
def greet: String = s"Hello, I'm $name"
}
// Usage
val person = new Person("Alice", 30) // 'new' required for class
Data Classes → Case Classes
# Python
from dataclasses import dataclass
@dataclass
class Point:
x: float
y: float
@dataclass(frozen=True)
class ImmutablePoint:
x: float
y: float
// Scala - case class is idiomatic
case class Point(x: Double, y: Double)
// Case classes are immutable by default
// They auto-generate: equals, hashCode, toString, copy, apply
// Usage
val p = Point(1.0, 2.0) // No 'new' needed for case class
val p2 = p.copy(x = 3.0) // Creates new instance with x changed
Properties
# Python
class Circle:
def __init__(self, radius: float):
self._radius = radius
@property
def radius(self) -> float:
return self._radius
@radius.setter
def radius(self, value: float):
if value < 0:
raise ValueError("Radius must be non-negative")
self._radius = value
@property
def area(self) -> float:
return 3.14159 * self._radius ** 2
// Scala
class Circle(private var _radius: Double) {
require(_radius >= 0, "Radius must be non-negative")
def radius: Double = _radius
def radius_=(value: Double): Unit = {
require(value >= 0, "Radius must be non-negative")
_radius = value
}
def area: Double = math.Pi * _radius * _radius
}
// Idiomatic Scala: prefer immutable case class
case class Circle(radius: Double) {
require(radius >= 0, "Radius must be non-negative")
def area: Double = math.Pi * radius * radius
}
Inheritance
# Python
class Animal:
def __init__(self, name: str):
self.name = name
def speak(self) -> str:
raise NotImplementedError
class Dog(Animal):
def speak(self) -> str:
return f"{self.name} says woof!"
class Cat(Animal):
def speak(self) -> str:
return f"{self.name} says meow!"
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.
- 9d ago First seen · 377 lines · 49 tokens per session scan A 71b407928329
python-scala-oop is a skill published in the GitHub repository benchflow-ai/skillsbench (1,764 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 49 tokens to every session and 2,040 once invoked, about $0.0002 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 2026-09-03.
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