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 julianobarbosa/claude-code-skills --skill python-infrastructuregit clone --depth 1 https://github.com/julianobarbosa/claude-code-skillsWrote 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/julianobarbosa/claude-code-skills/python-infrastructure)<a href="https://agentmods.dev/skills/julianobarbosa/claude-code-skills/python-infrastructure"><img src="https://agentmods.dev/badge/skills/julianobarbosa/claude-code-skills/python-infrastructure/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/julianobarbosa/claude-code-skills/python-infrastructure"><img src="https://agentmods.dev/badge/skills/julianobarbosa/claude-code-skills/python-infrastructure.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 14 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00127 | $0.00739 |
| Opus 5 | $0.00063 | $0.00369 |
| Sonnet 5 | $0.00025 | $0.00148 |
| Haiku 4.5 | $0.00013 | $0.00074 |
Grade A, and why
python-infrastructure 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Infrastructure
System-reliability concerns for Python services, grouped because real code uses them together: a task you queue (background-jobs) needs retries (resilience) and instrumentation (observability) on the same call path.
Scope routing
| If you need to… | Read |
|---|---|
| Design a task queue, schedule recurring jobs, or run async workers (Celery, RQ, asyncio task pools) | References/background-jobs.md |
| Decide what to retry, with what backoff, and when to stop (tenacity patterns, idempotency, circuit breakers) | References/resilience.md |
| Instrument a service with structured logs, metrics, and traces (structlog, OpenTelemetry, the four golden signals) | References/observability.md |
Decision tree
Operation can fail transiently (network/IO/3rd-party API)?
-> resilience.md (retry policy)
Operation runs out-of-request (email, image processing, batch)?
-> background-jobs.md (queue + worker)
Need to know what's happening in production?
-> observability.md (logs/metrics/traces)
All three at once for one feature?
-> all three references, in that order.
Cross-skill boundaries
writing-python— how to write the function. This skill — how it survives in production.python-error-handling— what exception to raise. This skill — what to do when it's raised across a network boundary.python-resource-management— how to clean up resources (context managers). This skill — how to keep retrying when resources fail to acquire.
Gotchas
- Retry without backoff is a DoS amplifier. A failed downstream + immediate retry from N clients = traffic burst that keeps the downstream down. Default to exponential backoff + jitter from day one.
- Retrying non-idempotent operations duplicates side effects. A failed POST + retry can mean two charges. Always pair retry-on-failure with an idempotency key OR mark the operation non-retryable.
- Synchronous code inside an async worker blocks the event loop. A "fast"
requestscall in an asyncio worker kills throughput. Use the async client (httpx,aiohttp) or run sync code in an executor. - Structured logs and metrics serve different audiences. Logs answer "what happened to this one request"; metrics answer "what's happening across all requests". Don't try to derive one from the other — instrument both.
- Trace context propagation needs explicit plumbing across the queue boundary. Pushing a task to Celery loses the current trace unless you serialize the trace context into the task headers and restore it in the worker. Read the OpenTelemetry-Celery propagator docs before assuming it "just works".
What ships with it
3 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.
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.
- 8d ago First seen · 44 lines · 127 tokens per session scan A bc866064c831
python-infrastructure is a skill published in the GitHub repository julianobarbosa/claude-code-skills (10 stars, last pushed 16d ago), licensed MIT. It adds 127 tokens to every session and 739 once invoked, about $0.0006 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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