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-librariesgit 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-libraries)<a href="https://agentmods.dev/skills/xuansenpa1/skillrevise/python-scala-libraries"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/python-scala-libraries/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-libraries"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/python-scala-libraries.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 | $0.00054 | $0.02397 |
| Opus 5 | $0.00027 | $0.01198 |
| Sonnet 5 | $0.00011 | $0.00479 |
| Haiku 4.5 | $0.00005 | $0.00240 |
Grade B, and why
python-scala-libraries scanned grade B with 2 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
response = requests.post( "https://api.example.com/data", Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.get("https://api.example.com/data") This is a copy
100% identical to python-scala-libraries — 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 — 447 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python to Scala Library Mappings
JSON Handling
# Python
import json
data = {"name": "Alice", "age": 30}
json_str = json.dumps(data)
parsed = json.loads(json_str)
# With dataclass
from dataclasses import dataclass, asdict
@dataclass
class Person:
name: str
age: int
person = Person("Alice", 30)
json.dumps(asdict(person))
// Scala - circe (most popular)
import io.circe._
import io.circe.generic.auto._
import io.circe.syntax._
import io.circe.parser._
case class Person(name: String, age: Int)
val person = Person("Alice", 30)
val jsonStr: String = person.asJson.noSpaces
val parsed: Either[Error, Person] = decode[Person](jsonStr)
// Scala - play-json
import play.api.libs.json._
case class Person(name: String, age: Int)
implicit val personFormat: Format[Person] = Json.format[Person]
val json = Json.toJson(person)
val parsed = json.as[Person]
Date and Time
# Python
from datetime import datetime, date, timedelta
import pytz
now = datetime.now()
today = date.today()
specific = datetime(2024, 1, 15, 10, 30)
formatted = now.strftime("%Y-%m-%d %H:%M:%S")
parsed = datetime.strptime("2024-01-15", "%Y-%m-%d")
tomorrow = now + timedelta(days=1)
# Timezone
utc_now = datetime.now(pytz.UTC)
// Scala - java.time (recommended)
import java.time._
import java.time.format.DateTimeFormatter
val now = LocalDateTime.now()
val today = LocalDate.now()
val specific = LocalDateTime.of(2024, 1, 15, 10, 30)
val formatted = now.format(DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss"))
val parsed = LocalDate.parse("2024-01-15")
val tomorrow = now.plusDays(1)
// Timezone
val utcNow = ZonedDateTime.now(ZoneOffset.UTC)
val instant = Instant.now()
File Operations
# Python
from pathlib import Path
import os
# Reading
with open("file.txt", "r") as f:
content = f.read()
lines = f.readlines()
# Writing
with open("file.txt", "w") as f:
f.write("Hello")
# Path operations
path = Path("dir/file.txt")
path.exists()
path.parent
path.name
path.suffix
list(Path(".").glob("*.txt"))
os.makedirs("new/dir", exist_ok=True)
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 · 447 lines · 54 tokens per session scan B aab0e5fdfc33
python-scala-libraries is a skill published in the GitHub repository xuansenpa1/skillrevise (56 stars, last pushed 7d ago), licensed MIT. It adds 54 tokens to every session and 2,397 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). It is 100% identical to python-scala-libraries, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
matlab
Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
pennylane
Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with…
dd-code-generation
Use pup CLI for immediate Datadog operations or generate code for integration into applications.
rocm-kernels
Provides guidance for writing and benchmarking optimized Triton kernels for AMD GPUs (MI355X, R9700) on ROCm, targeting HuggingFace diffusers (LTX-Video, SD3, FLUX) and transformers. Core kernels: RMSNorm, RoPE 3D, GEGLU, AdaLN. Includes XCD swizzle, autotune, diffusers integration patterns, and LTX-Video pipeline…
holoscan-install-wheel
Install Holoscan SDK Python wheel via pip into a venv. Use for Python installs; not for native C++/apt or Conda installs.
typing-exclusion-worker
Python typing exclusion worker: remove assigned mypy exclusion modules in small scoped batches, fix typing issues, run validation, and produce a structured completion summary. Use when running parallel typing-debt workers or when asked to remove modules from pyproject mypy exclusion overrides.