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 agentmods add skills/benjaminastera/antigravity-awesome-skills/async-python-patternsnpx skills add benjaminasterA/antigravity-awesome-skills --skill async-python-patternsgit clone --depth 1 https://github.com/benjaminasterA/antigravity-awesome-skillsWhat 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 | $0.00040 | $0.00327 |
| Opus 5 | $0.00020 | $0.00163 |
| Sonnet 5 | $0.00008 | $0.00065 |
| Haiku 4.5 | $0.00004 | $0.00033 |
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 2d 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
94% identical to async-python-patterns — 4 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.
What ships with it
1 file 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.
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.
- 2d ago First seen · 42 lines · 40 tokens per session scan A ca47d0098367
async-python-patterns is a skill published in the GitHub repository benjaminasterA/antigravity-awesome-skills (228 stars, last pushed 17d ago), licensed MIT. It adds 40 tokens to every session and 327 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to async-python-patterns, differing in 4 lines, and is treated as a copy.
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