Files
kubeshark/skills/README.md
Alon Girmonsky 10dbedf356 Add KFL and Network RCA skills (#1875)
* Add KFL and Network RCA skills

Introduce the skills/ directory with two Kubeshark MCP skills:

- network-rca: Retrospective traffic analysis via snapshots, dissection,
  KFL queries, PCAP extraction, and trend comparison
- kfl: Complete KFL2 (Kubeshark Filter Language) reference covering all
  supported protocols, variables, operators, and filter patterns

Update CLAUDE.md with skill authoring guidelines, structure conventions,
and the list of available Kubeshark MCP tools.

* Optimize skills and add shared setup reference

- network-rca: cut repeated metaphor, add list_api_calls example response,
  consolidate use cases, remove unbuilt composability section, extract
  setup reference to references/setup.md (409 → 306 lines)
- kfl: merge thin protocol sections, fix map_get inconsistency, add
  negation examples, move capture source to reference doc
- kfl2-reference: add most-commonly-used variables table, add inline
  filter examples per protocol section
- Add skills/README.md with usage and contribution guidelines

* Add plugin infrastructure and update READMEs

- Add .claude-plugin/plugin.json and marketplace.json for Claude Code
  plugin distribution
- Add .mcp.json bundling the Kubeshark MCP configuration
- Update skills/README.md with plugin install, manual install, and
  agent compatibility sections
- Update mcp/README.md with AI skills section and install instructions
- Restructure network-rca skill into two distinct investigation routes:
  PCAP (no dissection, BPF filters, Wireshark/compliance) and
  Dissection (indexed queries, AI-driven analysis, payload inspection)

* Remove CLAUDE.md from tracked files

Content now lives in skills/README.md, mcp/README.md, and the skills themselves.

* Add README to .claude-plugin directory

* Reorder MCP config: default mode first, URL mode for no-kubectl

* Move AI Skills section to top of MCP README

* Reorder manual install: symlink first

* Streamline skills README: focus on usage and contributing

* Enforce KFL skill loading before writing filters

- network-rca: require loading KFL skill before constructing filters,
  suggest installation if unavailable
- kfl: set user-invocable: false (background knowledge skill), strengthen
  description to mandate loading before any filter construction

* Move KFL requirement to top of Dissection route

* Add strict fallback: only use exact examples if KFL skill unavailable

* Add clone step to manual installation

* Use $PWD/kubeshark paths in manual install examples

* Add mkdir before symlinks, simplify paths

* Move prerequisites before installation

---------

Co-authored-by: Alon Girmonsky <alongir@Alons-Mac-Studio.local>
2026-03-18 15:31:32 -07:00

3.7 KiB

Kubeshark AI Skills

Open-source AI skills that work with the Kubeshark MCP. Skills teach AI agents how to use Kubeshark's MCP tools for specific workflows like root cause analysis, traffic filtering, and forensic investigation.

Skills use the open Agent Skills format and work with Claude Code, OpenAI Codex CLI, Gemini CLI, Cursor, and other compatible agents.

Available Skills

Skill Description
network-rca Network Root Cause Analysis. Retrospective traffic analysis via snapshots, with two investigation routes: PCAP (for Wireshark/compliance) and Dissection (for AI-driven API-level investigation).
kfl KFL2 (Kubeshark Filter Language) expert. Complete reference for writing, debugging, and optimizing CEL-based traffic filters across all supported protocols.

Prerequisites

All skills require the Kubeshark MCP:

# Claude Code
claude mcp add kubeshark -- kubeshark mcp

# Without kubectl access (direct URL)
claude mcp add kubeshark -- kubeshark mcp --url https://kubeshark.example.com

For Claude Desktop, add to claude_desktop_config.json:

{
  "mcpServers": {
    "kubeshark": {
      "command": "kubeshark",
      "args": ["mcp"]
    }
  }
}

Installation

Install as a Claude Code plugin directly from GitHub:

/plugin marketplace add kubeshark/kubeshark
/plugin install kubeshark

Skills appear as /kubeshark:network-rca and /kubeshark:kfl. The plugin also bundles the Kubeshark MCP configuration automatically.

Option 2: Clone and run

git clone https://github.com/kubeshark/kubeshark
cd kubeshark
claude

Skills trigger automatically based on your conversation.

Option 3: Manual installation

Clone the repo (if you haven't already), then symlink or copy the skills:

git clone https://github.com/kubeshark/kubeshark
mkdir -p ~/.claude/skills

# Symlink to stay in sync with the repo (recommended)
ln -s kubeshark/skills/network-rca ~/.claude/skills/network-rca
ln -s kubeshark/skills/kfl ~/.claude/skills/kfl

# Or copy to your project (project scope only)
mkdir -p .claude/skills
cp -r kubeshark/skills/network-rca .claude/skills/
cp -r kubeshark/skills/kfl .claude/skills/

# Or copy for personal use (all your projects)
cp -r kubeshark/skills/network-rca ~/.claude/skills/
cp -r kubeshark/skills/kfl ~/.claude/skills/

Contributing

We welcome contributions — whether improving an existing skill or proposing a new one.

  • Suggest improvements: Open an issue or PR with changes to an existing skill's SKILL.md or reference docs. Better examples, clearer workflows, and additional filter patterns are always appreciated.
  • Add a new skill: Open an issue describing the use case first. New skills should follow the structure below and reference Kubeshark MCP tools by exact name.

Skill structure

skills/
└── <skill-name>/
    ├── SKILL.md              # Required. YAML frontmatter + markdown body.
    └── references/           # Optional. Detailed reference docs.
        └── *.md

Guidelines

  • Keep SKILL.md under 500 lines. Use references/ for detailed content.
  • Use imperative tone. Reference MCP tools by exact name.
  • Include realistic example tool responses.
  • The description frontmatter should be generous with trigger keywords.

Planned skills

  • api-security — OWASP API Top 10 assessment against live or snapshot traffic.
  • incident-response — 7-phase forensic incident investigation methodology.
  • network-engineering — Real-time traffic analysis, latency debugging, dependency mapping.