observability-k8s-investigation

observability-k8s-investigation is a skill for Claude Code from elastic/agent-skills. It costs 90 tokens per session (7,167 once invoked), scanned A, original, Apache-2.0.

A troubleshooting guide for Kubernetes, a system for running containerised applications. It uses OpenTelemetry monitoring data, events, logs, and application signals to investigate failures across workloads, machines, and cluster control components.

In plain words
What is it for?
Use it to investigate pod and node failures, resource exhaustion, image-pull errors, admission rejections, and unusual autoscaling behaviour.
Why use it?
It helps connect symptoms such as restarting pods, memory kills, full nodes, failed image downloads, rejected deployments, and autoscaling problems to their likely causes.

Skill for Claude Code ✓ vendor

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

Part of the elastic-observability plugin — 4 skills shipped together

Good fit Use it to investigate pod and node failures, resource exhaustion, image-pull errors, admission rejections, and unusual autoscaling behaviour.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/elastic/agent-skills/k8s-investigation
About the project

Elastic Agent Skills is a library of instruction packages that teach AI coding agents how to work with Elastic products, including Elasticsearch, Kibana, Elastic Observability, and Elastic Security. Developers use the skills for tasks such as API work, Kibana content management, observability, and security workflows. The catalogue entries are skills and plugins from this library.

elastic/agent-skills · 575 stars · on GitHub

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 elastic/agent-skills --skill k8s-investigation
Clone the repo
git clone --depth 1 https://github.com/elastic/agent-skills

Made for: Claude Code.

Or install elastic-observability, the plugin that ships this one along with the rest of its 4 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 observability-k8s-investigation

README.md
[![agentmods](https://agentmods.dev/badge/skills/elastic/agent-skills/k8s-investigation/github.svg)](https://agentmods.dev/skills/elastic/agent-skills/k8s-investigation)
Your own site
<a href="https://agentmods.dev/skills/elastic/agent-skills/k8s-investigation"><img src="https://agentmods.dev/badge/skills/elastic/agent-skills/k8s-investigation/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 observability-k8s-investigation

Your own site · 80×15
<a href="https://agentmods.dev/skills/elastic/agent-skills/k8s-investigation"><img src="https://agentmods.dev/badge/skills/elastic/agent-skills/k8s-investigation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 90 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,167 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 12 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Prompt Injection · line 28
    Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.
    Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
  • medium Prompt Injection · line 38
    Subtle instructions detected that may alter agent decision-making or introduce hidden biases.
    Fix: Review content for implicit steering or bias. Ensure instructions are explicit and align with the skill's stated purpose.
  • medium Memory Poisoning · line 194
    Skill attempts to fill the context window with filler content, displacing legitimate instructions and safety constraints. This can degrade agent performance or bypass safety boundaries.
    Fix: Implement context-window management that detects and rejects padding or stuffing attempts. Prioritize system instructions over user-injected content.
  • medium Memory Poisoning · line 197
    Skill attempts to fill the context window with filler content, displacing legitimate instructions and safety constraints. This can degrade agent performance or bypass safety boundaries.
    Fix: Implement context-window management that detects and rejects padding or stuffing attempts. Prioritize system instructions over user-injected content.
  • medium Memory Poisoning · line 199
    Skill attempts to fill the context window with filler content, displacing legitimate instructions and safety constraints. This can degrade agent performance or bypass safety boundaries.
    Fix: Implement context-window management that detects and rejects padding or stuffing attempts. Prioritize system instructions over user-injected content.
  • medium Prompt Injection · line 194
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 194
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 196
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 197
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 197
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 199
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 200
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
How audits are shown
Origin original No closer match found 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 $0.00090 $0.07167
Opus 5 $0.00045 $0.03583
Sonnet 5 $0.00018 $0.01433
Haiku 4.5 $0.00009 $0.00717

Measured 7d ago against content hash ed36956876e7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

observability-k8s-investigation 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

plugins/observability/skills/k8s-investigation/SKILL.md · 492 lines

How it starts

The opening of the file, as written. The whole thing — 492 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Kubernetes Investigation

Diagnose Kubernetes issues using OTel telemetry collected via EDOT (Elastic Distribution of OpenTelemetry) and the kube-stack collector. Correlate cluster state, pod runtime metrics, K8s events, application logs, and APM to identify root cause across the workload, node, and control-plane layers.

Environment Configuration

This skill executes Elasticsearch operations through the elastic CLI. If the elastic CLI is not installed, tell the user what it is needed for. Do not guess credentials, call the HTTP API directly, or attempt other workarounds.

This skill references operations in HTTP-shorthand form (e.g., GET /, GET /_cat/indices, GET /{index}/_mapping, GET /{index}/_settings/index.mode, POST /_query). The Operations table at the end of this document maps each shorthand to the equivalent elastic CLI command — always use the CLI rather than calling the HTTP API directly.

Analysis without cluster access

The CLI check above gates querying the cluster — it does not gate analysis. When the user has already supplied the evidence in their question (metric values, counts, status reasons, log lines, alert payloads, configuration), reason from that evidence and deliver the conclusion.

When you genuinely do need data the user has not provided, still say what you would check and how — name the specific query, index, and field that would settle the question — and then ask for CLI setup. An answer that names the check is useful without a cluster; one that only asks for setup is not.

Every ES|QL query in this skill and in references/query-recipes.md runs via POST /_query. Alert state is read with GET kbn:/api/alerting/rules/_find. Field-presence checks use GET /<index>/_mapping or GET /_field_caps. The Operations table maps each to its elastic CLI equivalent.

Read the full file on GitHub · 492 lines

Files

What ships with it

2 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.

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. 7d ago Changed · +26 lines ed36956876e7
  2. 11d ago First seen · 466 lines · 90 tokens per session scan A a667bf302a00

Subscribe to this mod's changes

observability-k8s-investigation is a skill published in the GitHub repository elastic/agent-skills (575 stars, last pushed today), licensed Apache-2.0. It adds 90 tokens to every session and 7,167 once invoked, about $0.0005 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 2026-08-30.

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