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 0xDarkMatter/claude-mods --skill python-async-opsgit clone --depth 1 https://github.com/0xDarkMatter/claude-modsWrote 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/0xdarkmatter/claude-mods/python-async-ops)<a href="https://agentmods.dev/skills/0xdarkmatter/claude-mods/python-async-ops"><img src="https://agentmods.dev/badge/skills/0xdarkmatter/claude-mods/python-async-ops/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/0xdarkmatter/claude-mods/python-async-ops"><img src="https://agentmods.dev/badge/skills/0xdarkmatter/claude-mods/python-async-ops.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 | $0.00040 | $0.01157 |
| Opus 5.5 | $0.00016 | $0.00463 |
| Sonnet 5.5 | $0.00008 | $0.00231 |
| Haiku 4.5 | $0.00004 | $0.00116 |
Grade A, and why
python-async-ops scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
async def fetch(url: str) -> str: How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Async Patterns
Asyncio patterns for concurrent Python programming.
When to Use Async vs Sync
| Use Async When | Use Sync When |
|---|---|
| I/O-bound operations (HTTP, DB, files) | CPU-bound computations |
| High concurrency (100s+ connections) | Simple scripts, one-off tasks |
| WebSocket/streaming connections | Small data processing |
| Microservices with network calls | Single sequential operations |
Decision tree:
- Is it CPU-bound? → Sync (or multiprocessing)
- Is it I/O-bound with high concurrency? → Async
- Is it simple I/O with few connections? → Sync is fine
Core Concepts
import asyncio
# Coroutine (must be awaited)
async def fetch(url: str) -> str:
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
return await response.text()
# Entry point
async def main():
result = await fetch("https://example.com")
return result
asyncio.run(main())
Pattern 1: Concurrent with gather
async def fetch_all(urls: list[str]) -> list[str]:
"""Fetch multiple URLs concurrently."""
async with aiohttp.ClientSession() as session:
tasks = [fetch_one(session, url) for url in urls]
return await asyncio.gather(*tasks, return_exceptions=True)
Pattern 2: Bounded Concurrency
async def fetch_with_limit(urls: list[str], limit: int = 10):
"""Limit concurrent requests."""
semaphore = asyncio.Semaphore(limit)
async def bounded_fetch(url):
async with semaphore:
return await fetch_one(url)
return await asyncio.gather(*[bounded_fetch(url) for url in urls])
Pattern 3: TaskGroup (Python 3.11+)
async def process_items(items):
"""Structured concurrency with automatic cleanup."""
async with asyncio.TaskGroup() as tg:
for item in items:
tg.create_task(process_one(item))
# All tasks complete here, or exception raised
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/async-project-template.py 3.6 KB runs code
- references/aiohttp-patterns.md 6.1 KB
- references/concurrency-patterns.md 6.0 KB
- references/debugging-async.md 5.8 KB
- references/error-handling.md 12 KB
- references/mixing-sync-async.md 5.7 KB
- references/performance.md 10 KB
- references/production-patterns.md 10 KB
- scripts/find-blocking-calls.sh 1.4 KB runs code
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.
- 1mo ago First seen · 178 lines · 40 tokens per session scan A 5af1ff44e78e
python-async-ops is a skill published in the GitHub repository 0xDarkMatter/claude-mods (71 stars, last pushed 7d ago), licensed MIT. It adds 40 tokens to every session and 1,157 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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