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Get Started Free →aiskillstore/storage-debug-instrumentation
Add comprehensive debugging and observability tooling for backend storage layers (PostgreSQL, ChromaDB) and startup metrics. Includes storage drift detection, raw data inspection endpoints, and a Next.js admin dashboard.
Passed 12 of 18 test cases with the skill, and 4 of 18 without it.
and 12 more in the full report
11 fixed4 passed either way6 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
After implementing the backend instrumentation files, what exact command should be executed to verify Python code formatting and quality checks?
| Checked | Without skill | With skill |
|---|---|---|
| Runs uvx ruff check backend to verify Python code formatting. | Missed | Passed |
The instructions your model reads when the skill loads.
Enable rapid diagnosis of storage state, synchronization health, and backend performance bottlenecks by exposing:
app/services/startup_metrics.py, app/main.py, app/vector_store.py, app/database.py, app/api/routes/debug.pyfrontend/lib/api.ts, frontend/app/debug/page.tsxFile: backend/app/services/startup_metrics.py
StartupMetrics class to record phase timingsrecord_event(name, started_at, detail, metadata) for phase captureadd_note(key, value) for arbitrary annotationsstartup_metrics for app-wide useFile: backend/app/vector_store.py
startup_metricsVectorStore.__init__(), wrap initialization with time.time() timerhost, port, collection, documentsFile: backend/app/main.py
startup_metrics.mark_app_started() at beginning of on_startup()record_event()cache_size, article_count, oldest_article_hoursstartup_metrics.mark_app_completed() at endadd_note()File: backend/app/database.py
test cases passed, vs 4 / 18 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.