python-resilience

Guidance for making Python programs handle temporary failures, using retries, increasing waits, time limits, and fault-tolerant decorators.

In plain words
What is it for?
Adding bounded retries to external calls, setting timeouts, handling rate limiting, and building more fault-tolerant Python services.
Why use it?
It helps services cope with network problems, unavailable dependencies, rate limits, and other failures that may clear up on their own.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/julien777z/agent-sync-action/python-resilience
Any agent
npx skills add julien777z/agent-sync-action --skill python-resilience
Clone the repo
git clone --depth 1 https://github.com/julien777z/agent-sync-action

Made for: Claude Code, Codex.

Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,377 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00047 $0.01377
Opus 5 $0.00023 $0.00688
Sonnet 5 $0.00009 $0.00275
Haiku 4.5 $0.00005 $0.00138

Measured 3d ago against content hash 76371da10a73, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

python-resilience scanned grade B 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 3d 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.

return httpx.post("https://api.example.com", json=request).json()
Origin

Copies of this mod

2 near-identical copies found in the catalogue:

.agents/skills/python-resilience/SKILL.md · 198 lines

How it starts

The opening of the file, as written. The whole thing — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Python Resilience Patterns

Build fault-tolerant Python applications that gracefully handle transient failures, network issues, and service outages. Resilience patterns keep systems running when dependencies are unreliable.

When to Use This Skill

  • Adding retry logic to external service calls
  • Implementing timeouts for network operations
  • Building fault-tolerant microservices
  • Handling rate limiting and backpressure
  • Creating infrastructure decorators
  • Designing circuit breakers

Core Concepts

1. Transient vs Permanent Failures

Retry transient errors (network timeouts, temporary service issues). Don't retry permanent errors (invalid credentials, bad requests).

2. Exponential Backoff

Increase wait time between retries to avoid overwhelming recovering services.

3. Jitter

Add randomness to backoff to prevent thundering herd when many clients retry simultaneously.

4. Bounded Retries

Cap both attempt count and total duration to prevent infinite retry loops.

Quick Start

from tenacity import retry, stop_after_attempt, wait_exponential_jitter

@retry(
    stop=stop_after_attempt(3),
    wait=wait_exponential_jitter(initial=1, max=10),
)
def call_external_service(request: dict) -> dict:
    return httpx.post("https://api.example.com", json=request).json()

Fundamental Patterns

Pattern 1: Basic Retry with Tenacity

Use the tenacity library for production-grade retry logic. For simpler cases, consider built-in retry functionality or a lightweight custom implementation.

from tenacity import (
    retry,
    stop_after_attempt,
    stop_after_delay,
    wait_exponential_jitter,
    retry_if_exception_type,
)

TRANSIENT_ERRORS = (ConnectionError, TimeoutError, OSError)

@retry(
    retry=retry_if_exception_type(TRANSIENT_ERRORS),
    stop=stop_after_attempt(5) | stop_after_delay(60),
    wait=wait_exponential_jitter(initial=1, max=30),
)
def fetch_data(url: str) -> dict:
    """Fetch data with automatic retry on transient failures."""
    response = httpx.get(url, timeout=30)
    response.raise_for_status()
    return response.json()

Read the full file on GitHub · 198 lines

Files

What ships with it

2 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.

Changes

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.

  1. 3d ago First seen · 198 lines · 47 tokens per session scan B 76371da10a73

Subscribe to this mod's changes

python-resilience is a skill published in the GitHub repository julien777z/agent-sync-action (5 stars, last pushed 4d ago), licensed MIT. It adds 47 tokens to every session and 1,377 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (sends data to an external url). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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