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 williamzujkowski/standards --skill service-meshgit clone --depth 1 https://github.com/williamzujkowski/standardsWrote 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/williamzujkowski/standards/service-mesh)<a href="https://agentmods.dev/skills/williamzujkowski/standards/service-mesh"><img src="https://agentmods.dev/badge/skills/williamzujkowski/standards/service-mesh/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/williamzujkowski/standards/service-mesh"><img src="https://agentmods.dev/badge/skills/williamzujkowski/standards/service-mesh.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 | $0.00036 | $0.04066 |
| Opus 5.5 | $0.00014 | $0.01626 |
| Sonnet 5.5 | $0.00007 | $0.00813 |
| Haiku 4.5 | $0.00004 | $0.00407 |
Grade A, and why
service-mesh 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 yesterday.
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
86% identical to graphql-api-design — 697 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.
How it starts
The opening of the file, as written. The whole thing — 772 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Service Mesh
Level 1: Quick Reference
What is a Service Mesh?
A service mesh is an infrastructure layer that provides transparent service-to-service communication with built-in observability, traffic management, and security features without requiring application code changes.
Core Components:
- Control Plane: Configuration and policy management (Istiod)
- Data Plane: Sidecar proxies handling traffic (Envoy)
- Service Identity: Certificate-based authentication (mTLS)
Key Benefits
1. Observability
- Automatic metrics collection (latency, throughput, errors)
- Distributed tracing (request flow visualization)
- Traffic topology and service dependencies
- Real-time dashboards (Kiali, Grafana)
2. Traffic Management
- Intelligent routing (canary, blue-green, A/B)
- Load balancing (round-robin, least-request, consistent hash)
- Traffic splitting and mirroring
- Request retries and timeouts
3. Security
- Automatic mutual TLS (mTLS) encryption
- Service-to-service authentication
- Fine-grained authorization policies
- Certificate rotation and management
4. Resilience
- Circuit breaking and outlier detection
- Rate limiting and quota management
- Fault injection for chaos testing
- Connection pooling
Istio vs Linkerd Comparison
| Feature | Istio | Linkerd |
|---|---|---|
| Proxy | Envoy (C++) | Linkerd2-proxy (Rust) |
| Resource Usage | Higher (100-200MB/pod) | Lower (10-20MB/pod) |
| Features | Comprehensive (100+ CRDs) | Focused (essential features) |
| Complexity | More complex setup | Simpler, faster setup |
| Multi-cluster | Full support | Basic support |
| Traffic Management | Advanced (mirroring, A/B) | Basic (canary, split) |
| Observability | Full stack (Kiali/Jaeger) | Built-in (Linkerd Viz) |
| Maturity | Production-ready (CNCF) | Production-ready (CNCF) |
Choose Istio when:
- Need advanced traffic management (mirroring, A/B testing)
- Multi-cluster or multi-cloud deployments
- Complex authorization requirements
- Established operations team
What ships with it
7 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.
- yesterday First seen · 772 lines · 36 tokens per session scan A b188433b091a
service-mesh is a skill published in the GitHub repository williamzujkowski/standards (18 stars, last pushed 1mo ago), licensed MIT. It adds 36 tokens to every session and 4,066 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to graphql-api-design, differing in 697 lines, and is treated as a copy.
Other skills, from other repositories
istio-expert
Expert-level Istio service mesh management, traffic control, security, and observability for Kubernetes. Use when the user mentions service mesh, Kubernetes, microservices, mTLS, or traffic management, or when the task involves Istio Architecture, VirtualService - Traffic Routing, Gateway - Ingress/Egress, or Security…
linkerd-expert
Expert-level Linkerd service mesh management, traffic control, reliability, and production operations. Use when the user mentions service mesh, Kubernetes, microservices, mTLS, or observability, or when the task involves Linkerd Architecture, Mesh Injection, Traffic Management, or Reliability Features.
k8s-observability
Vendor-neutral metrics + logs triage for Kubernetes workloads. Works with whichever backend RootCause is configured to use (GCP Stackdriver today; Prometheus / CloudWatch / Datadog as backends land).
k8s-autoscaling
Deep autoscaling diagnostics and tuning for three scaling paths: 1) Horizontal Pod Autoscaler (HPA), 2) Vertical Pod Autoscaler (VPA), 3) Karpenter node provisioning.
k8s-cost
Kubernetes cost optimization framework using usage evidence, right-sizing, autoscaling signal quality, storage hygiene, and node pool efficiency.
k8s-deploy
Safe Kubernetes deployment workflows using RootCause MCP tools only.