Agent skill · software engineering · n8n-io
n8n:create-instance-ai-eval
Authors a new Instance AI workflow eval case — written locally as JSON, calibrated against a real build, then pushed to the LangTracer suite CI runs — build cases, behaviour/process cases, credential cases, and seeded (mid-conversation) cases — with intent-driven expectations. Use when adding or changing an Instance AI workflow eval, or debugging why one is flaky.
Why this skill is useful
Adds specific JSON case authoring and calibration procedures for Instance AI workflows that the AI wouldn't reliably generate on its own.
What it needs
About 12k tokens when loaded. Last updated 2026-08-07. 199,638 stars on the source repository.
What this skill does
Create an Instance AI workflow eval Each eval is one JSON case — authored locally as a file in packages/@n8n/instance-ai/evaluations/data/workflows/ (the disk loader auto-discovers .json, no registration step), with a LangTracer suite as its durable home. Cases validate against harness/schema.ts (.strict() — unknown keys fail at load). The eval README is the exhaustive field reference; this skill is the opinionated how. Committing new case JSONs into the repo is no longer the recommended approach. Author the file locally (uncommitted), calibrate it against a real build, then push it to a lang-tracer suite with eval:langtracer-push (see Push to a lang-tracer suite) — --suite baseline for the consolidated corpus n8n CI runs, or a dedicated capability suite like agents. The suite is the home for the case; the eval CLI reads it back via --source langtracer. You still write the JSON file — it's just the input to the push, not a committed artifact. Seeded cases. An inline seed pushes with the case — the case-write API stores it verbatim, so the suite is its home like any other case. Only a seed.mode: "replay" case is refused (listed under skipped:): it's reconstructed from a LangSmith trace at run time, so it dies when that trace is pruned and has no durable home. Don't commit a replay case either — derive a synthetic case from it. See case-shapes.md. Set the autonomy level first Before you source, draft, or run anything, decide how hands-on the driver wants to be — and say it back. This skill runs at one of two autonomy levels. If the request makes the level clear ("just author and calibrate it yourself" vs. "stop me at each step", or an explicit mode), adopt it, state it in one line, and note how to override (e.g. "say 'stop me at calibration' to add a checkpoint"). If it's not clear, ask the driver one question offering the two levels before doing any work. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills n8n-io/create-instance-ai-eval