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 vasilyu1983/AI-Agents-public --skill qa-resiliencegit clone --depth 1 https://github.com/vasilyu1983/AI-Agents-publicWrote 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/vasilyu1983/ai-agents-public/qa-resilience)<a href="https://agentmods.dev/skills/vasilyu1983/ai-agents-public/qa-resilience"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/qa-resilience/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/vasilyu1983/ai-agents-public/qa-resilience"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/qa-resilience.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 | $0.00037 | $0.02156 |
| Opus 5 | $0.00018 | $0.01078 |
| Sonnet 5 | $0.00007 | $0.00431 |
| Haiku 4.5 | $0.00004 | $0.00216 |
Grade A, and why
qa-resilience 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 9d 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 — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QA Resilience
Use this skill when reliability work is about failure behavior, overload protection, degraded mode, or resilience testing. The goal is not "add retries everywhere." The goal is predictable failure handling, clear ownership, and testable recovery behavior.
Quick Reference
| Symptom | Start With |
|---|---|
| slow or hanging dependency | deadline and timeout budget |
| transient dependency failure | bounded retry with jitter and retry budget |
| sustained dependency failure | circuit breaker and fallback |
| rate-limited dependency | honor Retry-After, expose degraded behavior, and test quota paths intentionally |
| one bad host in a healthy pool | outlier detection or endpoint ejection |
| queue or pool saturation | bulkheads, concurrency limits, load shedding |
| non-critical feature outage | graceful degradation or feature flag fallback |
| resilience validation | deterministic fault injection before chaos |
When to Use This Skill
- retries, deadlines, hedging, breakers, bulkheads, and overload protection
- degraded-mode UX or API behavior
- service-mesh or gateway resilience policy
- chaos engineering, game days, DR drills, and fault injection
- release gates based on failure behavior, not only happy-path load tests
Route Elsewhere
- simple CRUD or single-process utilities -> ordinary error handling may be enough
- frontend-only failure behavior -> software-frontend
- service implementation details -> software-backend
- telemetry instrumentation -> qa-observability
- broader platform and incident operating model -> ops-devops-platform
Workflow
- Identify the critical user journeys and the dependencies that can break them.
- Define the contract per dependency:
- timeout or deadline budget
- retry ownership
- breaker or outlier policy
- concurrency and queue limits
- degraded behavior if the dependency is unavailable
- Decide where the policy lives:
- app code
- client library
- mesh or gateway
- Test in stages:
- deterministic fault injection
- staged chaos in non-production
- narrow prod canary or game day only with guardrails
- Define pass or fail signals:
- burn rate
- p95 or p99
- fallback rate
- breaker transitions
- shed volume
- recovery time
What ships with it
31 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.
- agents/openai.yaml 335 B
- assets/runbooks/resilience-runbook-template.md 1.1 KB
- assets/testing/fault-injection-playbook.md 836 B
- assets/testing/template-resilience-test-plan.md 3.6 KB
- data/sample-service-profile.json 4.3 KB
- data/sources.json 17 KB
- learnings.consolidated.md 589 B
- learnings.md 584 B
- references/ai-llm-resilience-failure-modes.md 6.7 KB
- references/bulkhead-isolation.md 7.9 KB
- references/cascading-failure-prevention.md 28 KB
- references/chaos-engineering-guide.md 4.0 KB
- references/chaos-tooling-recipes.md 20 KB
- references/circuit-breaker-patterns.md 9.4 KB
- references/deadlines-hedging.md 8.0 KB
- references/disaster-recovery-testing.md 17 KB
- references/distributed-systems-applied.md 45 KB
- references/gateway-mesh-resilience.md 2.8 KB
- references/graceful-degradation.md 14 KB
- references/health-check-patterns.md 9.8 KB
- references/idempotency-key-design.md 11 KB
- references/load-shedding-backpressure.md 17 KB
- references/reliability-theory-applied.md 39 KB
- references/resilience-checklists.md 1.8 KB
- references/resilience-telemetry.md 2.6 KB
- references/retry-patterns.md 8.0 KB
- references/slo-as-code.md 4.9 KB
- references/timeout-policies.md 8.0 KB
- scripts/README.md 3.9 KB
- scripts/resilience_checker.py 20 KB runs code
- scripts/test_resilience_checker.py 2.3 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.
- 9d ago First seen · 227 lines · 37 tokens per session scan A cad28d590b55
qa-resilience is a skill published in the GitHub repository vasilyu1983/AI-Agents-public (87 stars, last pushed 10d ago), licensed MIT. It adds 37 tokens to every session and 2,156 once invoked, about $0.0002 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.
Other skills, from other repositories
screen-reader-testing
Test web applications with screen readers including VoiceOver, NVDA, and JAWS. Use when validating screen reader compatibility, debugging accessibility issues, or ensuring assistive technology support.
web3-testing
Test smart contracts comprehensively using Hardhat and Foundry with unit tests, integration tests, and mainnet forking. Use when testing Solidity contracts, setting up blockchain test suites, or validating DeFi protocols.
temporal-python-testing
Test Temporal workflows with pytest, time-skipping, and mocking strategies. Covers unit testing, integration testing, replay testing, and local development setup. Use when implementing Temporal workflow tests or debugging test failures.
data-quality-frameworks
Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.
e2e-testing-patterns
Master end-to-end testing with Playwright and Cypress to build reliable test suites that catch bugs, improve confidence, and enable fast deployment. Use when implementing E2E tests, debugging flaky tests, or establishing testing standards.
workflow-patterns
Use this skill when implementing tasks according to Conductor's TDD workflow, handling phase checkpoints, managing git commits for tasks, or understanding the verification protocol.