ai-inference-service-mesh

ai-inference-service-mesh is a skill for Claude Code from lingxling/awesome-skills-cn. It costs 33 tokens per session (2,778 once invoked), scanned A, a copy of ai-inference-service-mesh, MIT.

A service-mesh guide for managing traffic between AI inference services. It covers Istio and Linkerd controls such as mutual TLS, which authenticates and encrypts service-to-service connections.

In plain words
What is it for?
Use it to set traffic rules by model version, customer, or priority; release new model backends gradually; enforce encryption; and improve resilience across clusters.
Why use it?
It helps secure internal AI requests and control how traffic moves between gateways, retrieval services, rerankers, and model servers. It also addresses failures, version rollouts, and overloaded GPU services without requiring changes to application code.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the agentic-awesome-skills plugin — 174 skills shipped together

Good fit Use it to set traffic rules by model version, customer, or priority; release new model backends gradually; enforce encryption; and improve resilience across clusters.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lingxling/awesome-skills-cn/ai-inference-service-mesh
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.

Any agent
npx skills add lingxling/awesome-skills-cn --skill ai-inference-service-mesh
Clone the repo
git clone --depth 1 https://github.com/lingxling/awesome-skills-cn

Made for: Claude Code.

Or install agentic-awesome-skills, the plugin that ships this one along with the rest of its 174 skills.

Wrote 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.

agentmods badge for ai-inference-service-mesh

README.md
[![agentmods](https://agentmods.dev/badge/skills/lingxling/awesome-skills-cn/ai-inference-service-mesh/github.svg)](https://agentmods.dev/skills/lingxling/awesome-skills-cn/ai-inference-service-mesh)
Your own site
<a href="https://agentmods.dev/skills/lingxling/awesome-skills-cn/ai-inference-service-mesh"><img src="https://agentmods.dev/badge/skills/lingxling/awesome-skills-cn/ai-inference-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.

agentmods 80×15 button for ai-inference-service-mesh

Your own site · 80×15
<a href="https://agentmods.dev/skills/lingxling/awesome-skills-cn/ai-inference-service-mesh"><img src="https://agentmods.dev/badge/skills/lingxling/awesome-skills-cn/ai-inference-service-mesh.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,778 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod 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 5.1 $0.00033 $0.02778
Opus 5.5 $0.00013 $0.01111
Sonnet 5.5 $0.00007 $0.00556
Haiku 4.5 $0.00003 $0.00278

Measured 10d ago against content hash 5a831ccc32cc, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ai-inference-service-mesh scanned grade A 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 10d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -s http://localhost:20001/kiali/api/namespaces/ai-inference/health | jq .
Origin

This is a copy

100% identical to ai-inference-service-mesh — 61 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.

antigravity-awesome-skills/plugins/agentic-awesome-skills-claude/skills/ai-inference-service-mesh/SKILL.md · 450 lines

How it starts

The opening of the file, as written. The whole thing — 450 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Inference Service Mesh

Apply Istio/Linkerd mesh controls to secure and optimize east-west AI traffic across inference microservices.

Why Mesh for AI

  • Enforce mTLS between gateway, retriever, reranker, and model services
  • Apply fine-grained traffic policies without app code changes
  • Run progressive delivery for model-serving backends
  • Observe latency hops for retrieval + generation chains
  • Route inference requests by model version, tenant, or priority tier
  • Protect expensive GPU-backed services from cascading failures

Prerequisites

# Install Istio with production profile
istioctl install --set profile=default \
  --set meshConfig.accessLogFile=/dev/stdout \
  --set meshConfig.defaultConfig.holdApplicationUntilProxyStarts=true

# Label inference namespace for sidecar injection
kubectl create namespace ai-inference
kubectl label namespace ai-inference istio-injection=enabled

# Verify installation
istioctl verify-install
istioctl analyze -n ai-inference

Core Patterns

mTLS Strict Mode Cluster-Wide

apiVersion: security.istio.io/v1beta1
kind: PeerAuthentication
metadata:
  name: default
  namespace: istio-system
spec:
  mtls:
    mode: STRICT
---
# Namespace-level override if needed for gradual rollout
apiVersion: security.istio.io/v1beta1
kind: PeerAuthentication
metadata:
  name: ai-inference-mtls
  namespace: ai-inference
spec:
  mtls:
    mode: STRICT
  portLevelMtls:
    # gRPC inference port
    8081:
      mode: STRICT
    # Prometheus metrics port - allow plaintext scraping
    9090:
      mode: PERMISSIVE

AuthorizationPolicy Per Service Account

apiVersion: security.istio.io/v1beta1
kind: AuthorizationPolicy
metadata:
  name: model-server-access
  namespace: ai-inference
spec:
  selector:
    matchLabels:
      app: model-server
  action: ALLOW
  rules:
  - from:
    - source:
        principals:
        - "cluster.local/ns/ai-inference/sa/api-gateway"
        - "cluster.local/ns/ai-inference/sa/orchestrator"
    to:
    - operation:
        methods: ["POST"]
        paths: ["/v1/predict", "/v1/embeddings", "/v2/models/*/infer"]
---
apiVersion: security.istio.io/v1beta1
kind: AuthorizationPolicy
metadata:
  name: deny-external-to-retriever
  namespace: ai-inference
spec:
  selector:
    matchLabels:
      app: vector-retriever
  action: DENY
  rules:
  - from:
    - source:
        notNamespaces: ["ai-inference"]

Read the full file on GitHub · 450 lines

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. 10d ago First seen · 450 lines · 33 tokens per session scan A 5a831ccc32cc

Subscribe to this mod's changes

ai-inference-service-mesh is a skill published in the GitHub repository lingxling/awesome-skills-cn (312 stars, last pushed 10d ago), licensed MIT. It adds 33 tokens to every session and 2,778 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to ai-inference-service-mesh, differing in 61 lines, and is treated as a copy.

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