Debug CI

Debug CI Failures

Use this skill when a Spellbook PR's CI tests fail and you need to diagnose the issue.

Step 1: Identify Which Sub-Project Failed

Each sub-project has its own CI workflow (daily_spellbook.yml, dex.yml, hourly_spellbook.yml, nft.yml, solana.yml, tokens.yml). All call the shared reusable workflow in .github/workflows/dbt_run.yml.

Check the PR's "Checks" tab to see which workflow(s) failed.

Step 2: Identify Which Step Failed

The CI pipeline runs these steps in order:

1. dbt seed — builds seed CSVs modified in the PR
2. dbt run initial model(s) — full historical build of modified models
3. dbt test initial model(s) — runs tests on the initial build
4. dbt run incremental model(s) — incremental run to test incremental logic
5. dbt test incremental model(s) — tests again post-incremental run

Click into the failed workflow run in the "Actions" tab to expand each step's logs.

Step 3: Diagnose Common Failures

Compile / Seed Failures

• Missing source or ref: Check that all source() and ref() calls point to valid models. Run dbt compile locally to verify.
• Missing seed metadata: If error says "Metadata is not found for ___", the seed likely doesn't exist in prod. Force a change on the seed file and include it in the PR so CI rebuilds it.

Model Run Failures

• SQL syntax errors: Check the compiled SQL in CI logs. Run dbt compile locally and test the output on Dune or via dune_query.py.
• Timeout (90-minute limit): Simplify the model, add tighter date filters, or check for missing partition filters.
• Schema not assigned: Every model must have schema in its config block. The CI check-schemas script will fail otherwise.

Test Failures

• unique_combination_of_columns failing: The model is producing duplicate rows for the unique key. Check your join logic, filters, and whether NULLs are present in key columns.
• not_null failing: A unique key column contains NULLs. Add coalesce() or filter out NULL rows.
• Seed test mismatch: Model output doesn't match seed expected values. Either update the seed CSV or fix the model logic. Query the CI test table on Dune to compare: dune.<ci_schema>.<model_name> (see Step 4).

Manifest / Extra Models Running

• More models running than expected: The manifest file on main may be out of date. Check if the commit manifest workflow in Actions completed successfully. If it's still running or failed, wait for it to finish, then re-trigger CI.
• Fix: The Dune team's commit manifest workflow auto-runs after merges. If it failed, the Dune team needs to re-run it.

Cluster Issues

• DuneSQL cluster down: The CI cluster may be offline. This requires the Dune team to fix internally. Check if other PRs are also failing.

Step 4: Query CI Test Tables

CI tables are available on Dune for ~24 hours after the run. Always use the dune. catalog prefix.

Current format (from dbt run initial model(s) logs):

select *
from dune.dune_spellbook_ci__tmp_pr<PR>_<run_id>_<attempt>.<model_name>
limit 100

Example: dune.dune_spellbook_ci__tmp_pr9744_27302471352_1.zeroex_bnb_api_fills

Legacy format:

select *
from dune.test_schema.git_dunesql_<GIT_HASH>_<schema>_<alias>
limit 100

For legacy tables, the suffix matches dbt schema + _ + alias (e.g. tokens.transfers → tokens_transfers). For current CI, use the dbt model name from logs.

Use these to:

• Verify data quality before expanding date ranges
• Compare CI output against production tables
• Debug seed test mismatches by joining CI table against the seed

If the CI table can't be found, the ~24-hour window may have elapsed. Re-run CI to rebuild.

Step 5: Common Fixes