Query Caveman Cloud telemetry with SQL

# Overview: list rules, limits, tables, and examples
cvm sql --schema

# Describe one table
cvm sql --schema requests

# Run a query with a time window
cvm sql "SELECT model, count() AS n FROM requests GROUP BY model" --window 7d

# Read SQL from a file
cvm sql -f spend.sql --from 2026-09-01 --to 2026-09-08 --format csv

# Use parameterized queries
cvm sql "SELECT count() FROM requests WHERE model = {m:String}" --param m=gpt-4o

 sql.query  {sql, params?, window?, from?, to?}
 sql.schema {table?}

SELECT
  model,
  count() AS requests,
  sum(input_tokens) AS total_input,
  sum(output_tokens) AS total_output,
  sum(spend_usd) AS total_spend
FROM requests
GROUP BY model
ORDER BY requests DESC

SELECT
  toDate(timestamp) AS day,
  workflow,
  sum(spend_usd) AS daily_spend,
  count() AS requests
FROM requests
GROUP BY day, workflow
ORDER BY day DESC, daily_spend DESC

SELECT
  trace_id,
  timestamp,
  latency_ms,
  model,
  agent,
  workflow
FROM requests
WHERE status = 'error' AND latency_ms > 5000
ORDER BY latency_ms DESC
LIMIT 100

SELECT
  tool_name,
  count() AS calls,
  count(DISTINCT trace_id) AS traces
FROM tool_events
GROUP BY tool_name
ORDER BY calls DESC

SELECT
  trace_id,
  sum(latency_ms) AS total_latency,
  max(timestamp) AS ended_at
FROM spans
GROUP BY trace_id
HAVING total_latency > 0
ORDER BY total_latency DESC
LIMIT 100

SELECT
  lower(r.workflow) AS workflow_slug,
  w.display_name,
  count() AS requests,
  sum(r.spend_usd) AS spend
FROM requests r
LEFT JOIN workloads w ON lower(r.workflow) = w.slug
GROUP BY workflow_slug, w.display_name
ORDER BY spend DESC

SELECT
  run_id,
  workbench_id,
  verdict,
  count() AS cases,
  sum(cost_usd) AS run_cost
FROM evals
GROUP BY run_id, workbench_id, verdict
ORDER BY run_cost DESC