tencentcloud-cls
Search and analyze Tencent Cloud CLS (Cloud Log Service) logs. Use whenever the user asks to: search logs, debug API errors, trace requests by trace ID, find 5xx errors, run CQL/SQL analytics over log topics, extract structured fields. Backed by the official tencentcloud-sdk-pyth
What it does
Tencent Cloud CLS (Log Service) — Search & Analysis
Search and run CQL / SQL analytics over Tencent Cloud CLS log topics.
Setup: See tencentcloud authentication. The SDK reads
TENCENTCLOUD_SECRET_ID/TENCENTCLOUD_SECRET_KEY/TENCENTCLOUD_REGIONfrom the environment.Companion skill: Use
tencentcloud-cls-alarmfor alarm policy / notice group / shield management. This skill is only about searching log content.
CLI (preferred)
The skill ships scripts/cls.py — a self-contained CLI for the most common operations.
CLS=$SKILL_DIR/scripts/cls.py
python3 $CLS topics # list topics
python3 $CLS search --topic <topic-id> --query 'level:ERROR' --time 1h
python3 $CLS search --topic <topic-id> --trace-id <uuid>
python3 $CLS search --topic <topic-id> --time 1d \
--query '* | SELECT api_name, count(*) AS cnt GROUP BY api_name ORDER BY cnt DESC LIMIT 20' \
--format json
--time accepts 30m / 1h / 6h / 1d / 7d. --query is CQL by default; pass --lucene to switch dialect. Append | SELECT ... GROUP BY ... to a query for SQL analytics.
For anything beyond what the CLI exposes (custom field projections, raw paginated walks, Context-based tailing) drop down to the SDK calls below.
When to Use
- Find recent errors / 5xx responses for a service
- Look up a single request by trace ID across multiple topics
- Run CQL filters (
status_code:>=500 AND service:"openai") - Run SQL analytics (
SELECT api_name, COUNT(*) GROUP BY api_name) - Chain trace logs to reconstruct a request lifecycle
- Extract specific fields for billing / audit reports
Dependencies
pip install tencentcloud-sdk-python
Quick start
import os
import json
from tencentcloud.common import credential
from tencentcloud.cls.v20201016 import cls_client, models
cred = credential.EnvironmentVariableCredential().get_credential()
client = cls_client.ClsClient(cred, os.environ["TENCENTCLOUD_REGION"])
Workflows
Discover topics
req = models.DescribeTopicsRequest()
resp = client.DescribeTopics(req)
for t in resp.Topics:
print(t.TopicId, t.TopicName, t.LogsetId)
Tip: ask the user for the topic ID up front. Topic IDs look like
751a7350-dc5d-41c3-a6ca-c178bae05807and aren't guessable from a service name.
Search logs (CQL)
import time
req = models.SearchLogRequest()
req.TopicId = "<topic-id>"
req.From = int((time.time() - 3600) * 1000) # 1 hour ago, ms epoch
req.To = int(time.time() * 1000)
req.Query = 'status_code:>=500 AND service:"openai"'
req.Limit = 100
req.Sort = "desc"
req.SyntaxRule = 1 # 1 = CQL, 0 = Lucene
resp = client.SearchLog(req)
for line in resp.Results:
fields = {f.Key: f.Value for f in line.LogJson and []} # see below
print(line.Time, line.PkgLogId, fields.get("status_code"), fields.get("api_name"))
CLS hands you
ResultswithLogJsonas a JSON string per record. Decode withjson.loads(line.LogJson)to get a flat dict of all the indexed fields the topic stores.
Look up a trace ID across multiple topics
TRACE_ID = "34341776-0835-422a-956d-ac8d5b404db1"
TOPICS = {
"trace": "<trace-topic-id>",
"api-usages": "<api-usages-topic-id>",
}
for label, topic_id in TOPICS.items():
req = models.SearchLogRequest()
req.TopicId = topic_id
req.From = int((time.time() - 86400) * 1000)
req.To = int(time.time() * 1000)
req.Query = f'trace_id:"{TRACE_ID}"'
req.Limit = 100
req.SyntaxRule = 1
resp = client.SearchLog(req)
print(f"--- {label}: {len(resp.Results)} records ---")
for line in resp.Results:
print(line.Time, line.LogJson)
SQL analytics
CLS supports a SQL-on-logs subset for aggregation. Append | <SQL> to a CQL filter:
req.Query = '* | SELECT api_name, count(*) AS cnt GROUP BY api_name ORDER BY cnt DESC LIMIT 20'
req.SyntaxRule = 1
resp = client.SearchLog(req)
# When the query has a `|`, results land in resp.Analysis (rows of column→value)
for row in resp.AnalysisResults or []:
print(row)
Tail recent logs
# Poll every 5s for new lines after the last cursor
last_cursor = None
while True:
req = models.SearchLogRequest()
req.TopicId = topic_id
req.From = int((time.time() - 30) * 1000)
req.To = int(time.time() * 1000)
req.Query = 'level:ERROR'
req.Limit = 100
req.Sort = "asc"
req.SyntaxRule = 1
if last_cursor:
req.Context = last_cursor
resp = client.SearchLog(req)
for line in resp.Results:
print(line.Time, line.LogJson)
last_cursor = resp.Context
time.sleep(5)
CQL cheatsheet
| Pattern | Meaning |
|---|---|
status_code:500 | exact match |
status_code:>=500 | range |
status_code:[500 TO 599] | range with bounds |
service:"openai" | quoted phrase (use for values containing spaces) |
NOT level:DEBUG | negation |
service:openai AND status_code:>=400 | conjunction |
(api:foo OR api:bar) | grouping |
| `* | SELECT ... GROUP BY ...` |
Pagination
CLS returns up to 1000 records per call. For larger result sets, iterate with Context:
all_records = []
context = None
while True:
req = models.SearchLogRequest()
req.TopicId = topic_id
req.From = ...
req.To = ...
req.Query = '...'
req.Limit = 1000
req.SyntaxRule = 1
if context:
req.Context = context
resp = client.SearchLog(req)
all_records.extend(resp.Results)
context = resp.Context
if not context or len(resp.Results) < 1000:
break
Error patterns
| Symptom | Likely cause |
|---|---|
InvalidParameter.QueryError | Quote phrases that contain : or spaces; check SyntaxRule matches the query |
LimitExceeded | Concurrent SearchLog calls exceed the 30-QPS quota — back off & retry |
OperationDenied.AccountIsolated | CLS service is suspended for billing — check the console |
Empty Results but logs visible in console | Time range is wrong (From / To are ms epoch, not seconds), or topic has different field names than the query expects |
Console links
- CLS console: https://console.cloud.tencent.com/cls/topic
- CQL syntax: https://www.tencentcloud.com/document/product/614/47044
- SQL analytics syntax: https://www.tencentcloud.com/document/product/614/58978
Capabilities
Install
Quality
deterministic score 0.45 from registry signals: · indexed on github topic:agent-skills · 7 github stars · SKILL.md body (6,493 chars)