Common Verify Report

Confirm the dd-trace/ddtrace package you added is declared in the dependency manifest the deploy installs from (the one identified in SKILL.md Phase 1e) — not merely present in your local environment. Grep that manifest for the package you added, or do a clean install into a throwaway env. This matters because a local pip install ddtrace followed by a successful uvicorn run passes the startup check below while the manifest is still missing the dependency — so the deploy would crash with ModuleNotFoundError even though local verification looked green.

For every backend runtime you instrumented, actually execute the instrumented entrypoint — do not rely on “the project’s start/dev script.” In a split frontend/backend repo there is often no single script that runs both halves, so “run the start script” can pass while never importing the backend at all. Load the module that contains your LLMObs.enable(...) / .init(...) so that init line runs:

• Python: from the same working directory the deploy uses (e.g. cd backend when the module lives under backend/, so PYTHONPATH/cwd match the deploy), run python -c "import app.main" (substitute the real module path), or boot the real start command (uvicorn app.main:app) and confirm it binds with no traceback. If you used the ddtrace-run / import ddtrace.auto alternative (no in-code LLMObs.enable(...) to import), boot with that wrapper instead — e.g. ddtrace-run uvicorn app.main:app.
• Node.js: node -e "require('./<entry>')" (or an import for an ESM entry), or boot the server entrypoint. If instrumentation is via NODE_OPTIONS='--import dd-trace/initialize.mjs', boot with that env set so the loader actually runs. For Next.js, run next build and confirm it completes without errors.

This is the step that catches a wrong import path or bad enable()/init() arguments — e.g. from ddtrace.llm_observability import LLMObs raising ModuleNotFoundError — which a passing manifest check will not surface.

If the app builds/runs successfully, tell the user where to look:

• LLM Observability: https://app.datadoghq.com/llm/traces?query=@ml_app:<mlAppName>

Report

Alongside this shape, summarize goal status in the human-readable message — see “Reporting goal status” in llmobs-python.md / llmobs-nodejs.md.