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 xuansenpa1/skillrevise --skill python-scala-functionalgit clone --depth 1 https://github.com/xuansenpa1/skillreviseWrote 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/xuansenpa1/skillrevise/python-scala-functional)<a href="https://agentmods.dev/skills/xuansenpa1/skillrevise/python-scala-functional"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/python-scala-functional/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/xuansenpa1/skillrevise/python-scala-functional"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/python-scala-functional.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00051 | $0.02369 |
| Opus 5 | $0.00026 | $0.01184 |
| Sonnet 5 | $0.00010 | $0.00474 |
| Haiku 4.5 | $0.00005 | $0.00237 |
Grade A, and why
python-scala-functional 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.
This is a copy
100% identical to python-scala-functional — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 371 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python to Scala Functional Programming Translation
Higher-Order Functions
# Python
def apply_twice(f, x):
return f(f(x))
def make_multiplier(n):
return lambda x: x * n
double = make_multiplier(2)
result = apply_twice(double, 5) # 20
// Scala
def applyTwice[A](f: A => A, x: A): A = f(f(x))
def makeMultiplier(n: Int): Int => Int = x => x * n
val double = makeMultiplier(2)
val result = applyTwice(double, 5) // 20
Decorators → Function Composition
# Python
def log_calls(func):
def wrapper(*args, **kwargs):
print(f"Calling {func.__name__}")
result = func(*args, **kwargs)
print(f"Finished {func.__name__}")
return result
return wrapper
@log_calls
def add(a, b):
return a + b
// Scala - function composition
def logCalls[A, B](f: A => B, name: String): A => B = { a =>
println(s"Calling $name")
val result = f(a)
println(s"Finished $name")
result
}
val add = (a: Int, b: Int) => a + b
val loggedAdd = logCalls(add.tupled, "add")
// Alternative: using by-name parameters
def withLogging[A](name: String)(block: => A): A = {
println(s"Calling $name")
val result = block
println(s"Finished $name")
result
}
Pattern Matching
# Python (3.10+)
def describe(value):
match value:
case 0:
return "zero"
case int(x) if x > 0:
return "positive int"
case int(x):
return "negative int"
case [x, y]:
return f"pair: {x}, {y}"
case {"name": name, "age": age}:
return f"{name} is {age}"
case _:
return "unknown"
// Scala - pattern matching is more powerful
def describe(value: Any): String = value match {
case 0 => "zero"
case x: Int if x > 0 => "positive int"
case _: Int => "negative int"
case (x, y) => s"pair: $x, $y"
case List(x, y) => s"list of two: $x, $y"
case m: Map[_, _] if m.contains("name") =>
s"${m("name")} is ${m("age")}"
case _ => "unknown"
}
// Case class pattern matching (preferred)
sealed trait Result
case class Success(value: Int) extends Result
case class Error(message: String) extends Result
def handle(result: Result): String = result match {
case Success(v) if v > 100 => s"Big success: $v"
case Success(v) => s"Success: $v"
case Error(msg) => s"Failed: $msg"
}
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 · 371 lines · 51 tokens per session scan A cf0986337f4b
python-scala-functional is a skill published in the GitHub repository xuansenpa1/skillrevise (56 stars, last pushed 7d ago), licensed MIT. It adds 51 tokens to every session and 2,369 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to python-scala-functional, differing in 0 lines, and is treated as a copy.
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