---
allowed-tools: Bash(wsl -- *)
description: 'Command: claude-stats (imported from Claude Code)'
name: cmd-claude-stats
---

## Claude 模型统计

查询 Claude 模型的**错误率**和**缓存率**，自动排除 `relay-pulse` 检测令牌。

### 参数 `$ARGUMENTS`

根据 `$ARGUMENTS` 确定日期范围：

| 传入格式 | 含义 |
|---------|------|
| （空） | 今天 |
| `2026-05-09` | 指定某一天 |
| `2026-05-01 2026-05-09` | 指定日期范围（含首尾两天） |
| `7d` | 最近 7 天 |

### 执行步骤

**第一步：根据参数计算日期过滤条件**

- `created_at` 字段是秒级 Unix 时间戳（bigint），用 `UNIX_TIMESTAMP('YYYY-MM-DD')` 转换
- 今天：`created_at >= UNIX_TIMESTAMP(CURDATE())`
- 某一天 `D`：`created_at >= UNIX_TIMESTAMP('D') AND created_at < UNIX_TIMESTAMP('D') + 86400`
- 范围 `D1` 到 `D2`：`created_at >= UNIX_TIMESTAMP('D1') AND created_at < UNIX_TIMESTAMP('D2') + 86400`
- 最近 N 天：`created_at >= UNIX_TIMESTAMP(DATE_SUB(CURDATE(), INTERVAL N-1 DAY))`

将计算好的条件替换到下面 SQL 中的 `{DATE_FILTER}` 占位符。

**第二步：上传 SQL 文件到服务器**

```bash
wsl -- bash -c "
cat > /tmp/claude_stats_error.sql << 'ENDSQL'
SELECT
  model_name,
  SUM(CASE WHEN type = 2 THEN 1 ELSE 0 END) as success,
  SUM(CASE WHEN type = 5 THEN 1 ELSE 0 END) as errors,
  COUNT(*) as total,
  ROUND(SUM(CASE WHEN type = 5 THEN 1 ELSE 0 END) * 100.0 / COUNT(*), 2) as error_rate_pct
FROM logs
WHERE {DATE_FILTER}
  AND model_name LIKE '%claude%'
  AND type IN (2, 5)
  AND token_name != 'relay-pulse'
GROUP BY model_name
ORDER BY total DESC;
ENDSQL

cat > /tmp/claude_stats_cache.sql << 'ENDSQL'
SELECT
  model_name,
  COUNT(*) as total_requests,
  SUM(prompt_tokens) as prompt_tokens,
  SUM(completion_tokens) as completion_tokens,
  SUM(CAST(IFNULL(JSON_UNQUOTE(JSON_EXTRACT(other, '$.cache_tokens')), 0) AS UNSIGNED)) as cache_read_tokens,
  SUM(CAST(IFNULL(JSON_UNQUOTE(JSON_EXTRACT(other, '$.cache_creation_tokens')), 0) AS UNSIGNED)) as cache_creation_tokens,
  SUM(CASE WHEN CAST(IFNULL(JSON_UNQUOTE(JSON_EXTRACT(other, '$.cache_tokens')), 0) AS UNSIGNED) > 0 THEN 1 ELSE 0 END) as cache_hit_requests,
  ROUND(
    SUM(CASE WHEN CAST(IFNULL(JSON_UNQUOTE(JSON_EXTRACT(other, '$.cache_tokens')), 0) AS UNSIGNED) > 0 THEN 1 ELSE 0 END) * 100.0 / COUNT(*),
    2
  ) as cache_hit_rate_pct,
  ROUND(
    (SUM(prompt_tokens) * 1.0
     + SUM(CAST(IFNULL(JSON_UNQUOTE(JSON_EXTRACT(other, '$.cache_tokens')), 0) AS UNSIGNED)) * 0.1
     + SUM(CAST(IFNULL(JSON_UNQUOTE(JSON_EXTRACT(other, '$.cache_creation_tokens')), 0) AS UNSIGNED)) * 1.25)
    * 100.0
    / NULLIF(
        SUM(prompt_tokens)
        + SUM(CAST(IFNULL(JSON_UNQUOTE(JSON_EXTRACT(other, '$.cache_tokens')), 0) AS UNSIGNED))
        + SUM(CAST(IFNULL(JSON_UNQUOTE(JSON_EXTRACT(other, '$.cache_creation_tokens')), 0) AS UNSIGNED)),
        0),
    2
  ) as cost_pct_of_full,
  ROUND(
    SUM(CAST(IFNULL(JSON_UNQUOTE(JSON_EXTRACT(other, '$.cache_creation_tokens')), 0) AS UNSIGNED)) * 1.0
    / NULLIF(SUM(CAST(IFNULL(JSON_UNQUOTE(JSON_EXTRACT(other, '$.cache_tokens')), 0) AS UNSIGNED)), 0),
    3
  ) as creation_to_read_ratio
FROM logs
WHERE {DATE_FILTER}
  AND type = 2
  AND model_name LIKE '%claude%'
  AND other IS NOT NULL
  AND token_name != 'relay-pulse'
GROUP BY model_name
ORDER BY total_requests DESC;
ENDSQL

cat > /tmp/claude_stats_errcode.sql << 'ENDSQL'
SELECT
  model_name,
  CAST(JSON_UNQUOTE(JSON_EXTRACT(other, '$.status_code')) AS UNSIGNED) as status_code,
  COUNT(*) as cnt,
  ROUND(COUNT(*) * 100.0 / SUM(COUNT(*)) OVER (PARTITION BY model_name), 1) as pct
FROM logs
WHERE {DATE_FILTER}
  AND type = 5
  AND model_name LIKE '%claude%'
  AND token_name != 'relay-pulse'
  AND other IS NOT NULL
GROUP BY model_name, status_code
ORDER BY model_name, cnt DESC;
ENDSQL

scp /tmp/claude_stats_error.sql root@139.180.189.205:/tmp/claude_stats_error.sql
scp /tmp/claude_stats_cache.sql root@139.180.189.205:/tmp/claude_stats_cache.sql
scp /tmp/claude_stats_errcode.sql root@139.180.189.205:/tmp/claude_stats_errcode.sql
"
```

**第三步：执行查询并展示结果**

```bash
wsl -- bash -c "ssh -o ConnectTimeout=20 -o ServerAliveInterval=10 root@139.180.189.205 'echo \"=== 错误率 ===\"; docker exec -i mysql mysql -uroot -pLanqi123456 new-api < /tmp/claude_stats_error.sql; echo; echo \"=== 缓存 ===\"; docker exec -i mysql mysql -uroot -pLanqi123456 new-api < /tmp/claude_stats_cache.sql; echo; echo \"=== 错误状态码分布 ===\"; docker exec -i mysql mysql -uroot -pLanqi123456 new-api < /tmp/claude_stats_errcode.sql' 2>&1 | grep -v 'Warning'"
```

### 字段说明

**错误率表：**
- `success` — 正常请求数（type=2）
- `errors` — 错误请求数（type=5）
- `error_rate_pct` — 错误率 %

**缓存率表：**
- `cache_hit_rate_pct` — **次数缓存率** = 有缓存命中的请求数 / 总请求数（最能反映缓存策略是否生效）
- `cost_pct_of_full` — **实际成本占比** = `(prompt × 1 + cache_read × 0.1 + cache_creation × 1.25) / (全量按原价计费)`，越低越省钱（Anthropic 标准定价：cache_read 是原价 10%，cache_creation 是原价 125%）
- `creation_to_read_ratio` — **缓存创建/读取比** = `cache_creation_tokens / cache_read_tokens`，比值高说明缓存频繁失效再重建，命中复用差

**错误状态码分布表：**
- `status_code` — HTTP 状态码（504=上游超时，429=限流，400=请求参数错误）
- `cnt` — 该状态码的错误次数
- `pct` — 占该模型全部错误的百分比

### 注意事项

- 日期以 OV 服务器（UTC+0）的时区为准，北京时间当天 08:00 后才对应同一自然日
- `relay-pulse` 是自动探活令牌，已从统计中排除