* 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>
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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
Option 1: Plugin (recommended)
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.mdor 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.mdunder 500 lines. Usereferences/for detailed content. - Use imperative tone. Reference MCP tools by exact name.
- Include realistic example tool responses.
- The
descriptionfrontmatter 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.