Seed Test Data
FreeGenerate reproducible test data for Langfuse environments.
Free · Opens the source repo
What Seed Test Data does
Seed Test Data is a command-line interface (CLI) tool designed for developers working with Langfuse, providing a straightforward way to generate deterministic test data for local environments using ClickHouse and Postgres. This tool eliminates the need for ad hoc scripts or manual data insertion, ensuring that test data is consistent and reproducible across various testing scenarios. By using this skill, developers can focus on building and testing their applications without the hassle of managing test data manually.
The CLI handles essential tasks such as environment loading, preflight checks, and writing data to ClickHouse or Postgres. It also includes readback verification to ensure that the data was written correctly. Additionally, the tool provides deep links to the user interface and a machine-readable JSON summary of the operation's results, making it easier to integrate with other tools or workflows. With its comprehensive set of commands, users can generate complex observation trees, realistic agent flows, and diverse session shapes tailored to their testing needs.
This skill is particularly useful for developers working on applications that require extensive testing with complex data structures. Whether you are testing frontend rendering, performance, or handling long sessions, Seed Test Data allows you to create the necessary scenarios without the overhead of manual data setup. The ability to generate specific data shapes and structures helps ensure that your application behaves as expected under various conditions, ultimately leading to more robust and reliable software.
However, this tool is not suitable for all testing scenarios. If your testing requirements do not involve Langfuse or if you prefer to manage your test data manually, this skill may not be necessary. Additionally, if your project does not utilize ClickHouse or Postgres, the benefits of this tool will be limited. It is best suited for those who are already integrated into the Langfuse ecosystem and require a reliable way to seed test data efficiently.
When to use it
Use this tool when you need to generate complex and reproducible test data for Langfuse in local development environments.
When not to use it
Avoid this skill if your project does not use Langfuse, ClickHouse, or Postgres, or if you prefer manual data management.
What you can build with it
Generate Complex Observation Trees
Create a highly detailed observation tree with thousands of observations and specific depth and breadth parameters.
Simulate Realistic Agent Flows
Generate a realistic agent flow over a timeline, useful for testing the interaction of various components in your application.
Produce Diverse Session Shapes
Create different session shapes for comprehensive testing, including chat, coding-agent, and media sessions.
How to install Seed Test Data
View source1. Install with the skills CLI
npx skills add langfuse/langfuse/seed-test-data --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by langfuseSeed Test Data
One-shot deterministic test data for local Langfuse. The CLI handles env loading, preflight checks, ClickHouse/Postgres writes, readback verification, and prints UI deep links plus a machine-readable JSON summary (last stdout line).
If anything fails, run doctor first
pnpm run seed -- doctor
Prints PASS/WARN/FAIL per dependency (Postgres, migrations, project, ClickHouse, v4 dev tables, Redis, MinIO, web app) with the exact fix command for every failure. Do not debug Docker/ClickHouse manually before running this.
Need → command
| I need... | Command |
|---|---|
| A very complex observation tree (v3) | pnpm run seed -- trace-tree --observations 5000 --depth 12 --breadth 500 |
| The same tree readable in the v4 events UI | add --v4 (writes events_full; events_core fills via MV) |
| Async parents whose subtree outlives their own span (subtree wall-clock duration badge) | add --async-parents to trace-tree (root + hub end immediately while children keep running) |
| A realistic agent flow over a timeline (graph view + scrubbable timeline) | pnpm run seed -- agent-timeline --turns 6 --v4 (LangGraph refine loop planner→retriever→generator→critic→loop, staggered in time; add --timing-only for the pure timing fallback) |
| A demo-grade, real-looking agent trace (videos, screenshots, docs) | pnpm run seed -- support-agent --v4 --id-prefix <hex> (one fixed, fully handcrafted support-copilot refund run: guardrails, parallel context fan-out, 3-turn ReAct loop with real payloads/costs; deterministic — reseed with a FRESH prefix for a clean take; the prefix is the trace id, so a hex prefix reads like production) |
| A plain trace with no agentic types (collapsed-by-default graph panel) | add --plain to trace-tree (SPAN/GENERATION/EVENT only) |
| An extremely DEEP single-chain trace (tree depth = observation count; layout stress) | pnpm run seed -- deep-chain --v4 (1401 sequential generations, each the sole child of the previous — the mis-parented-instrumentation shape from LFE-10959 that collapses tree/timeline layouts; --observations N to change depth) |
| A super tough session (v3 legacy session view) | pnpm run seed -- long-session --traces 300 --observations-per-trace 8 |
| Diverse v4 session shapes (chat / coding-agent / mixed / media) for the session-detail view | pnpm run seed -- session-shapes --shape all (the agent shape has I/O on AGENT/TOOL with no GENERATION — pre-LFE-10520 the "first generation" default rendered empty cards for it; the current "All observations with I/O" default renders it correctly; v4 on by default) |
| Session messages carrying Langfuse media references (inline image, several refs in one message, bare refs in a content array, link-only payload) | pnpm run seed -- session-shapes --shape media — uploads the image/audio/pdf fixtures to MinIO and links them to the observation, so the inline chip and the "Media" strip both resolve (LFE-14815, LFE-9577) |
| Many traces for list/filter performance | pnpm run seed -- many-traces --count 100000 --days 14 |
| Long-window v4 traffic with cost/latency/token OUTLIERS (outlier chart strip, LFE-14451) | pnpm run seed -- outlier-traffic --days 90 (diurnal base load + deterministic spikes + hour-long ×8-latency incidents; root AGENT + GENERATION carrying cost + TOOL per trace; v4 on by default) |
| Scores with spaces in the name (filter/grammar testing) | pnpm run seed -- scored-traces --traces 24 --v4 |
| Lots of scores on every node (dense score badges, tree-row overflow testing) | add --scores-per-node 12 to trace-tree (N distinct scores per observation; try --depth 2 --breadth 44 for many tall sibling rows) |
| Extra trace tags, incl. mixed case/accents (tag filter ordering) | add --tags "Zebra,apple,Ärger" to trace-tree (comma-separated, appended to the scenario's own tags) |
| Varied human-annotation queues (annotate UI / keyboard testing) | pnpm run seed -- annotation-queue --core-items 12 (creates a "core types" queue covering every score-field render path + an "edge cases" queue with archived/stale/partial scores and observation/session/deleted/completed items) |
| Huge/malformed/unicode payloads | pnpm run seed -- trace-tree --payload-bytes 1000000 --payload-style malformed (styles: json, text, malformed, unicode, bignum, base64) |
| Big integers beyond 2^53-1 (number-precision testing) | pnpm run seed -- trace-tree --observations 1 --payload-style bignum |
| Huge base64 data-URI in ChatML IO (multimodal crash shape, LFE-10152) | pnpm run seed -- trace-tree --observations 30 --payload-bytes 20000000 --payload-style base64 --v4 (one unbroken multi-MB base64 token in trace + root-observation IO; max 50 MB) |
| See all scenarios and flags | pnpm run seed -- list --json |
| Predict without writing | add --dry-run |
Contract
- Last stdout line is a JSON summary:
traceIds,sessionIds,counts,verified(ClickHouse readback),links(UI deep links). Use--jsonto suppress progress logs. Non-zero exit = data did not land; the error includes afix:line. - Deterministic: same
--seed(default 42) and flags → same ids (ids never contain dates), with timestamps anchored to the current UTC day. Re-running within the same day overwrites in place; a later-day re-run updates the same ids with re-anchored timestamps (the previous day's rows persist under their old dates until then). Independent copies come only from--id-prefix. - Default project is the seeded
7a88fb47-b4e2-43b8-a06c-a5ce950dc53a(logindemo@langfuse.com/password); override with--project. - Open the printed
linksin the browser to verify visually. The v4 events-backed UI is the per-user "Fast (Preview)" sidebar toggle, orLANGFUSE_MIGRATION_V4_WRITE_MODE=events_onlyserver-side.
Extending
Add a scenario in packages/shared/scripts/seeder/scenarios/: a plain
function using the deterministic Rng (never Math.random), register it in
scenarios/index.ts, and update the table in
packages/shared/scripts/seeder/AGENTS.md and this skill. Scenario names,
flags, and JSON keys are additive-only contracts. Design rationale:
packages/shared/scripts/seeder/README.md.
Frequently asked questions about Seed Test Data
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