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 ancoleman/ai-design-components --skill implementing-service-meshgit clone --depth 1 https://github.com/ancoleman/ai-design-componentsWrote 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/ancoleman/ai-design-components/implementing-service-mesh)<a href="https://agentmods.dev/skills/ancoleman/ai-design-components/implementing-service-mesh"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/implementing-service-mesh.svg" alt="Measured on agentmods" 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 | $0.00065 | $0.02670 |
| Opus 5 | $0.00032 | $0.01335 |
| Sonnet 5 | $0.00013 | $0.00534 |
| Haiku 4.5 | $0.00006 | $0.00267 |
Grade B, and why
implementing-service-mesh scanned grade B with 2 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.
Downloads and executes remote codemediumSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -L https://istio.io/downloadIstio | sh - Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -L https://istio.io/downloadIstio | sh - How it starts
The opening of the file, as written. The whole thing — 466 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Service Mesh Implementation
Purpose
Configure and deploy service mesh infrastructure for Kubernetes environments. Enable secure service-to-service communication with mutual TLS, implement traffic management policies, configure authorization controls, and set up progressive delivery strategies. Abstracts network complexity while providing observability, security, and resilience for microservices.
When to Use
Invoke this skill when:
- "Set up service mesh with mTLS"
- "Configure Istio traffic routing"
- "Implement canary deployments"
- "Secure microservices communication"
- "Add authorization policies to services"
- "Traffic splitting between versions"
- "Multi-cluster service mesh setup"
- "Configure ambient mode vs sidecar"
- "Set up circuit breaker configuration"
- "Enable distributed tracing"
Service Mesh Selection
Choose based on requirements and constraints.
Istio Ambient (Recommended for most):
- 8% latency overhead with mTLS (vs 166% sidecar mode)
- Enterprise features, multi-cloud, advanced L7 routing
- Sidecar-less L4 (ztunnel) + optional L7 (waypoint)
Linkerd (Simplicity priority):
- 33% latency overhead (lowest sidecar)
- Rust-based micro-proxy, automatic mTLS
- Best for small-medium teams, easy adoption
Cilium (eBPF-native):
- 99% latency overhead, kernel-level enforcement
- Advanced networking, sidecar-less by design
- Best for eBPF infrastructure, future-proof
For detailed comparison matrix and architecture trade-offs, see references/decision-tree.md.
Core Concepts
Data Plane Architectures
Sidecar: Proxy per pod, fine-grained L7 control, higher overhead Sidecar-less: Shared node proxies (Istio Ambient) or eBPF (Cilium), lower overhead
Istio Ambient Components:
- ztunnel: Per-node L4 proxy for mTLS
- waypoint: Optional per-namespace L7 proxy for HTTP routing
Traffic Management
Routing: Path, header, weight-based traffic distribution Resilience: Retries, timeouts, circuit breakers, fault injection Load Balancing: Round robin, least connections, consistent hash
What ships with it
13 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.
- examples/cilium/network-policy.yaml 3.1 KB
- examples/istio/canary-deployment.yaml 2.4 KB
- examples/istio/mtls-authorization.yaml 1.6 KB
- examples/linkerd/traffic-split.yaml 2.4 KB
- outputs.yaml 19 KB
- references/cilium-patterns.md 14 KB
- references/decision-tree.md 9.9 KB
- references/istio-patterns.md 15 KB
- references/linkerd-patterns.md 13 KB
- references/multi-cluster.md 13 KB
- references/progressive-delivery.md 15 KB
- references/security-patterns.md 14 KB
- references/troubleshooting.md 15 KB
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 · 466 lines · 65 tokens per session scan B 67cd33294202
implementing-service-mesh is a skill published in the GitHub repository ancoleman/ai-design-components (519 stars, last pushed 9mo ago), licensed MIT. It adds 65 tokens to every session and 2,670 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
kubectl-basics
A guide to kubectl, the command-line tool used to manage Kubernetes clusters, which run containerized applications.
nemoclaw-setup
Install and configure NVIDIA NemoClaw (sandboxed OpenClaw agent platform) on Linux. Handles cloudflared tunnels, Docker cgroup fixes, OpenShell, sandbox creation, remote access via Cloudflare Tunnel, and known bug workarounds. Use whenever the user mentions installing NemoClaw, setting up OpenClaw, configuring an…
configmap-secret
Kubernetes ConfigMap 与 Secret.
deployment
Kubernetes Deployment 管理.
service-ingress
Kubernetes Service 与 Ingress.
kubernetes-specialist
Use when deploying or managing Kubernetes workloads. Invoke to create deployment manifests, configure pod security policies, set up service accounts, define network isolation rules, debug pod crashes, analyze resource limits, inspect container logs, or right-size workloads. Use for Helm charts, RBAC policies…