Logs, cost and SQL

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cycls logs my-agent --query 'jsonPayload.error_id="abc12345"'

cycls logs my-agent                 # the most recent batch, then exit
cycls logs my-agent -f              # tail, polling every 2 seconds
cycls logs my-agent -s 30m          # a narrower window: 30m, 24h, 7d
cycls logs my-agent -q 'jsonPayload.level="error"'
cycls logs my-agent -q 'jsonPayload.user_id="user_2yY1..."' -f

cycls cost my-agent
# my-agent  $0.027126  (4 turns, 24h)

cycls cost my-agent --since 7d
cycls cost my-agent --month 2026-09
cycls cost my-agent --by user        # or chat, or model

llm = cycls.LLM().price(input=3, output=15, cache_read=0.30, cache_write=6)

cycls sql 'SELECT ...'       # inline
cycls sql -f query.sql       # from a file
cat query.sql | cycls sql    # from stdin

-- Model spend per user, last 30 days
SELECT JSON_VALUE(json_payload, '$.user_id')                    AS user_id,
       SUM(CAST(JSON_VALUE(json_payload, '$.cost') AS FLOAT64)) AS spend
FROM logs
WHERE JSON_VALUE(json_payload, '$.level') = 'usage'
  AND timestamp > TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 30 DAY)
GROUP BY user_id
ORDER BY spend DESC

-- Infrastructure cost per deployment, last 30 days
SELECT resource.name AS deployment, ROUND(SUM(cost), 4) AS usd
FROM billing
WHERE usage_start_time > TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 30 DAY)
GROUP BY deployment
ORDER BY usd DESC

-- Tool latency at p95, last 7 days
SELECT JSON_VALUE(json_payload, '$.tool') AS tool,
       APPROX_QUANTILES(CAST(JSON_VALUE(json_payload, '$.ms') AS INT64), 100)[OFFSET(95)] AS p95_ms,
       COUNT(*) AS calls
FROM logs
WHERE JSON_VALUE(json_payload, '$.level') = 'tool_call'
  AND timestamp > TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 7 DAY)
GROUP BY tool
ORDER BY p95_ms DESC

cycls.log("cap_hit", user=context.user, chat_id=context.chat_id,
          kind="user_free_monthly", count=entry["count"])