generate-sample-data

A tool for creating synthetic security events and alerts, meaning made-up data that resembles real security activity.

In plain words
What is it for?
Populating Elastic Security dashboards, testing detection rules, demonstrating workflows, and setting up proofs of concept.
Why use it?
It provides test data without requiring real incidents or waiting for live alerts.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/elastic/example-mcp-app-security/generate-sample-data
Any agent
npx skills add elastic/example-mcp-app-security --skill generate-sample-data
Clone the repo
git clone --depth 1 https://github.com/elastic/example-mcp-app-security

Made for: Claude Code, Codex.

Per session 55 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 366 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00055 $0.00366
Opus 5 $0.00028 $0.00183
Sonnet 5 $0.00011 $0.00073
Haiku 4.5 $0.00006 $0.00037

Measured 2d ago against content hash 541b6f475c93, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

generate-sample-data 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 2d 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.

skills/generate-sample-data/SKILL.md · 41 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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. 2d ago First seen · 41 lines · 55 tokens per session scan A 541b6f475c93

Subscribe to this mod's changes

generate-sample-data is a skill published in the GitHub repository elastic/example-mcp-app-security (22 stars, last pushed 12d ago), with no licence file. It adds 55 tokens to every session and 366 once invoked, about $0.0003 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.

Related

Other skills, from other repositories

21st-ui

Find, install, and generate UI with 21st.dev. Use when the user asks for a UI component (pricing table, hero, navbar, dashboard, form, etc.), wants design inspiration, needs a brand logo as an SVG component, or wants to generate new UI from a prompt.

21st-dev/magic-mcp · 63 tokens

building-detection-rules-with-sigma

Builds vendor-agnostic detection rules using the Sigma rule format for threat detection across SIEM platforms including Splunk, Elastic, and Microsoft Sentinel. Use when creating portable detection logic from threat intelligence, mapping rules to MITRE ATT&CK techniques, or converting community Sigma rules into…

adriannoes/awesome-agentic-ai · 77 tokens

repo-context

Use repo-context-mcp tools to map, search, and pack repository context before large edits or PR review.

nduc99911/repo-context-mcp · 25 tokens

webmcp-nexus

当接入 webmcp-nexus-sdk 的项目中需要新增 WebMCP 工具函数、将现有业务方法改造为 WebMCP 工具函数,或配置 vite-plugin-webmcp-nexus / webpack-plugin-webmcp-nexus 时使用本技能。本技能约束工具函数的签名、JSDoc、TS 类型写法,并提供零风险的改造流程(仅改签名与注释,不动原方法业务逻辑)。触发示例:"新增一个 WebMCP 工具"、"把这个函数改造成能被 AI Agent 调用的工具"、"让 xxx 函数接入 WebMCP"、"配置 webmcp 构建插件"。.

alibaba/webmcp-nexus · 159 tokens

MCP Integration Assistant

Helps design and implement Model Context Protocol (MCP) server integrations for AI agents.

Notysoty/openagentskills · 23 tokens

MCP Server Builder

Step-by-step guidance for creating a new MCP server with FastMCP or the TypeScript SDK — tool definitions, resource handlers, error responses, and usage examples.

Notysoty/openagentskills · 38 tokens