CodeceptJS Run Analysis

After npx codeceptjs run, the trace artifacts land in output/. This skill is the playbook for reading them efficiently — pulling out the right step, the right file, and the right slice of a giant HTML snapshot using bash tools rather than re-running the test through MCP.

There's no single end goal — pick the use case that matches the situation. The foundations (where artifacts live, how to read them, what tools to reach for) apply to all of them.

Foundations

Ensure aiTrace is on

The whole skill leans on output/trace_<TestName>_<hash>/trace.md and its sibling artifacts. Confirm plugins: { aiTrace: { enabled: true } } in the active config (run codeceptjs-fundamentals if you don't already know). Without aiTrace there are screenshots and pageInfo dumps at most — useful but partial; suggest enabling and re-running before deep analysis.

The MCP run_step_by_step tool is now interactive (pauses after every step; agent advances via continue) and no longer auto-writes a per-run artifact bundle. aiTrace is the only source of per-step trace files now — for ad-hoc run_code and snapshot calls you still get a single-shot artifact set under output/trace_run_code_* / output/snapshot_*.

Locate traces

Trace directories are output/trace_<TestName>_<short-hash>/; reruns produce a new dir per run. When the right trace isn't obvious, sort by modification time and take the most recent (ls -dt) — almost always the run you just kicked off.

Read trace.md first

trace.md is the index — each step block links to its screenshot/HTML/ARIA/console. Focus on the step marked failed; if no failure is explicitly marked, jump to the last step in the trace — execution usually stops where the failure happened. When more than one step shows failed, the first is usually the cause; the rest are cascading side effects.