name: analyze-cloud-costs description: | Analyze Langfuse Cloud infrastructure cost structure using Metabase cost marts. Use when asked about cloud spend, AWS versus ClickHouse cost splits, cost drivers by provider/service/usage type/account, daily cost per tracing event, infra cost dashboards, or cost regressions visible in Metabase.
Analyze Cloud Costs
Overview
Use this skill for evidence-backed Langfuse Cloud cost analysis. The primary source is the Metabase infra cost dashboard and its production cost marts; the deliverable should name the time window, query grain, top drivers, and caveats.
Workflow
- Clarify the question and choose the grain:
- Headline daily totals: total, AWS, ClickHouse, tracing events, and cost per 100k events.
- Cost structure: provider, service, usage type, operation, account, and day.
- Driver or regression analysis: compare a recent complete-day window against a prior baseline.
- Load
references/cost-marts.mdfor table IDs, field IDs, query examples, and caveats. - Use the Metabase MCP. If the Metabase tools are not visible, discover them with tool search before falling back to manual interpretation.
- Prefer complete UTC days. Avoid treating current-day AWS cost as final because AWS CUR rows can arrive late.
- Start broad, then drill down:
- Provider split.
- Service split within the dominant provider.
- Usage type, operation, and account split for the top services.
- Daily trend when explaining change over time.
- Report only what the queried data supports. If a requested slice is absent, say that no rows were found for that slice instead of inventing a driver.
Query Rules
- Use
mcp__metabase__.queryfor quick reads. Useconstruct_queryplusexecute_querywhen you need to inspect or reuse the opaque query. - Pass
filters,aggregations,group_by, andfieldsas JSON arrays. Some tool schemas may display these as strings; if that happens, serialize the same arrays without changing their shape. - Keep limits explicit and small enough for analysis. Use pagination only when the continuation token is needed.
- Include the Metabase dashboard link or query result context in the final answer when useful.
Output Expectations
Summarize:
- Time window and whether it uses complete UTC days.
- Total cost and provider split when relevant.
- Top cost drivers by service, usage type, operation, or account.
- Trend or baseline comparison when the user asks "why did this change?"
- Caveats, especially incomplete current-day AWS data and ClickHouse credit labeling in the unified mart.