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 cxcscmu/SkillLearnBench --skill python-scala-syntax-mappinggit clone --depth 1 https://github.com/cxcscmu/SkillLearnBenchWrote 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/cxcscmu/skilllearnbench/python-scala-syntax-mapping)<a href="https://agentmods.dev/skills/cxcscmu/skilllearnbench/python-scala-syntax-mapping"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/python-scala-syntax-mapping.svg" alt="Measured on agentmods" 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 | $0.00030 | $0.00403 |
| Opus 5 | $0.00015 | $0.00201 |
| Sonnet 5 | $0.00006 | $0.00081 |
| Haiku 4.5 | $0.00003 | $0.00040 |
Grade A, and why
python-scala-syntax-mapping 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 3d 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.
What it actually says
Python to Scala Syntax Mapping
Enums
Python Enum -> Scala sealed trait + case objects or Enumeration:
// Preferred: sealed trait for pattern matching exhaustiveness
sealed abstract class TokenType(val value: String)
object TokenType {
case object STRING extends TokenType("string")
case object NUMERIC extends TokenType("numeric")
}
Dataclasses (frozen=True) -> Case Classes
// Python: @dataclass(frozen=True) with default fields
// Scala: case class (immutable by default)
case class Token(value: String, tokenType: TokenType, metadata: Map[String, Any] = Map.empty)
TypeVar -> Type Parameters
// Python: T = TypeVar("T") -> [T]
// Python: T_co = TypeVar(covariant) -> [+T]
// Python: T_contra = TypeVar(contra) -> [-T]
// Python: NumericT = TypeVar("NumericT", int, float, Decimal) -> type class or union
Protocol -> Trait (structural typing)
// Python Protocol -> Scala trait
trait Tokenizable {
def toToken: String
}
Optional / Union
// Python: Optional[X] -> Scala: Option[X]
// Python: X | None -> Scala: Option[X]
// Python: Union[A, B] -> Scala: Either[A, B] or sealed trait or overloaded methods
Default Mutable Args
Python allows mutable defaults (anti-pattern). Scala avoids this:
// Python: def __init__(self, opts: dict = {}):
// Scala: def this(opts: Map[String, Any] = Map.empty)
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.
- 3d ago First seen · 56 lines · 30 tokens per session scan A c4402bcd0171
python-scala-syntax-mapping is a skill published in the GitHub repository cxcscmu/SkillLearnBench (83 stars, last pushed 1mo ago), licensed MIT. It adds 30 tokens to every session and 403 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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