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 beel-collab/presets.dev --skill async-python-patternsgit clone --depth 1 https://github.com/beel-collab/presets.devWrote 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/beel-collab/presets.dev/async-python-patterns)<a href="https://agentmods.dev/skills/beel-collab/presets.dev/async-python-patterns"><img src="https://agentmods.dev/badge/skills/beel-collab/presets.dev/async-python-patterns/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/beel-collab/presets.dev/async-python-patterns"><img src="https://agentmods.dev/badge/skills/beel-collab/presets.dev/async-python-patterns.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 | $0.00029 | $0.00404 |
| Opus 5.5 | $0.00012 | $0.00162 |
| Sonnet 5.5 | $0.00006 | $0.00081 |
| Haiku 4.5 | $0.00003 | $0.00040 |
Grade A, and why
async-python-patterns 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 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.
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
91% identical to async-python-patterns — 11 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.
What it actually says
Async Python Patterns
Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems.
Use this skill when
- Building async web APIs (FastAPI, aiohttp, Sanic)
- Implementing concurrent I/O operations (database, file, network)
- Creating web scrapers with concurrent requests
- Developing real-time applications (WebSocket servers, chat systems)
- Processing multiple independent tasks simultaneously
- Building microservices with async communication
- Optimizing I/O-bound workloads
- Implementing async background tasks and queues
Do not use this skill when
- The workload is CPU-bound with minimal I/O.
- A simple synchronous script is sufficient.
- The runtime environment cannot support asyncio/event loop usage.
Instructions
- Clarify workload characteristics (I/O vs CPU), targets, and runtime constraints.
- Pick concurrency patterns (tasks, gather, queues, pools) with cancellation rules.
- Add timeouts, backpressure, and structured error handling.
- Include testing and debugging guidance for async code paths.
- If detailed examples are required, open
resources/implementation-playbook.md.
Refer to resources/implementation-playbook.md for detailed patterns and examples.
Resources
resources/implementation-playbook.mdfor detailed patterns and examples.
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
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 · 49 lines · 29 tokens per session scan A 6f8774bb3d64
async-python-patterns is a skill published in the GitHub repository beel-collab/presets.dev (3 stars, last pushed 5mo ago), licensed MIT. It adds 29 tokens to every session and 404 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to async-python-patterns, differing in 11 lines, and is treated as a copy.
Other skills, from other repositories
python-development
You MUST activate this skill when working on Python projects.
async-python-patterns
Master Python asyncio, concurrent programming, and async/await patterns for high-performance applications. Use when building async APIs, concurrent systems, or I/O-bound applications requiring non-blocking operations.
fastapi-templates
Create production-ready FastAPI projects with async patterns, dependency injection, and comprehensive error handling. Use when building new FastAPI applications or setting up backend API projects.
python-resource-management
Python resource management with context managers, cleanup patterns, and streaming. Use when managing connections, file handles, implementing cleanup logic, or building streaming responses with accumulated state.
python-background-jobs
Python background job patterns including task queues, workers, and event-driven architecture. Use when implementing async task processing, job queues, long-running operations, or decoupling work from request/response cycles.
ecc-api-patterns
FastAPI best practices covering project structure, Pydantic v2 schemas, dependency injection, async handlers, authentication, authorization, transactional service layers, and testing with httpx and pytest. Use when building or reviewing FastAPI apps — Pydantic schemas, dependencies, async handlers, auth, or tests.