Agentic Plugin Marketplace is a collection of reusable plugins, agents, skills, commands, and rules for coding-agent tools including Claude Code, Codex CLI, Cursor, OpenCode, Antigravity CLI, and GitHub Copilot. It is for developers assembling agentic workflows across multiple harnesses from shared Markdown sources, and the catalogue entries are examples or subsets of those workflow components.
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 wshobson/agents --skill service-mesh-observabilitygit clone --depth 1 https://github.com/wshobson/agentsWrote 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/wshobson/agents/service-mesh-observability)<a href="https://agentmods.dev/skills/wshobson/agents/service-mesh-observability"><img src="https://agentmods.dev/badge/skills/wshobson/agents/service-mesh-observability/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/wshobson/agents/service-mesh-observability"><img src="https://agentmods.dev/badge/skills/wshobson/agents/service-mesh-observability.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00043 | $0.00547 |
| Opus 5 | $0.00022 | $0.00273 |
| Sonnet 5 | $0.00009 | $0.00109 |
| Haiku 4.5 | $0.00004 | $0.00055 |
Grade A, and why
service-mesh-observability 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 7d 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.
Copies of this mod
5 near-identical copies found in the catalogue:
- service-mesh-observability — 100% identical, 0 lines differ
- service-mesh-observability — 86% identical, 330 lines differ
- service-mesh-observability — 86% identical, 325 lines differ
- service-mesh-observability — 86% identical, 339 lines differ
- service-mesh-observability — 86% identical, 325 lines differ
How it starts
The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Service Mesh Observability
Complete guide to observability patterns for Istio, Linkerd, and service mesh deployments.
When to Use This Skill
- Setting up distributed tracing across services
- Implementing service mesh metrics and dashboards
- Debugging latency and error issues
- Defining SLOs for service communication
- Visualizing service dependencies
- Troubleshooting mesh connectivity
Core Concepts
1. Three Pillars of Observability
┌─────────────────────────────────────────────────────┐
│ Observability │
├─────────────────┬─────────────────┬─────────────────┤
│ Metrics │ Traces │ Logs │
│ │ │ │
│ • Request rate │ • Span context │ • Access logs │
│ • Error rate │ • Latency │ • Error details │
│ • Latency P50 │ • Dependencies │ • Debug info │
│ • Saturation │ • Bottlenecks │ • Audit trail │
└─────────────────┴─────────────────┴─────────────────┘
2. Golden Signals for Mesh
| Signal | Description | Alert Threshold |
|---|---|---|
| Latency | Request duration P50, P99 | P99 > 500ms |
| Traffic | Requests per second | Anomaly detection |
| Errors | 5xx error rate | > 1% |
| Saturation | Resource utilization | > 80% |
Templates and detailed worked examples
Full template library and detailed worked examples live in references/details.md. Read that file when you need the concrete templates.
Best Practices
Do's
- Sample appropriately - 100% in dev, 1-10% in prod
- Use trace context - Propagate headers consistently
- Set up alerts - For golden signals
- Correlate metrics/traces - Use exemplars
- Retain strategically - Hot/cold storage tiers
Don'ts
- Don't over-sample - Storage costs add up
- Don't ignore cardinality - Limit label values
- Don't skip dashboards - Visualize dependencies
- Don't forget costs - Monitor observability costs
What ships with it
1 file 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.
- 7d ago First seen · 65 lines · 43 tokens per session scan A 0aaa93e88b7f
service-mesh-observability is a skill published in the GitHub repository wshobson/agents (39,533 stars, last pushed 3d ago), licensed MIT. It adds 43 tokens to every session and 547 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.
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