name: cloudflare-worker-logs description: Query and analyze Cloudflare Workers logs. Use for debugging workers, checking error rates, viewing request logs. Activates with phrases like "check worker logs", "what errors are in the worker", "cloudflare logs", "worker observability".
Cloudflare Worker Logs
Query historical logs from Cloudflare Workers using the Workers Observability API.
Requirements
Requires environment variables (should be defined in env already; if not, available via uv run poe init-secrets):
CLOUDFLARE_ACCOUNT_IDCLOUDFLARE_API_TOKEN
Real-time Logs
For real-time log streaming (not historical queries), use wrangler tail instead:
cd terraform/cloudflare && wrangler tail llms --format pretty
This requires a terminal session that stays open.
Available Scripts
All scripts are in the scripts/ directory relative to this skill. Run them with:
uv run scripts/<script_name>.py [args]
cf_workers_list.py
List all Workers in the Cloudflare account. If you only need details of a single Worker, use cf_worker_get.py instead.
uv run scripts/cf_workers_list.py
No arguments required.
cf_worker_get.py
Get the details of a Cloudflare Worker.
uv run scripts/cf_worker_get.py <script_name>
Arguments:
script_name(required): The name of the worker script to retrieve
cf_observability_keys.py
Find keys in the Workers Observability data.
Best Practices:
- Set a high limit (1000+) to ensure you see all available keys
- Add the
$metadata.servicefilter to narrow results to a specific Worker
Troubleshooting:
- If expected fields are missing, verify the Worker is actively logging
- For empty results, try broadening your time range
uv run scripts/cf_observability_keys.py [options]
Options:
--minutes N: Time range in minutes (default: 60, max: 10080 for 7 days)--limit N: Max keys to return (default: 100, set high like 1000 for comprehensive list)--key-needle PATTERN: Pattern to match key names--key-needle-regex: Treat key-needle as regex--needle TEXT: General text search in log content--needle-regex: Treat needle as regex--filter KEY:OP:TYPE:VALUE: Filter (can be repeated)
Example:
uv run scripts/cf_observability_keys.py --limit 1000 --filter '$metadata.service:eq:string:llms'
cf_observability_values.py
Find values in the Workers Observability Data.
Troubleshooting:
- For no results, verify the field exists using
cf_observability_keys.pyfirst - If expected values are missing, try broadening your time range
uv run scripts/cf_observability_values.py <key> [options]
Arguments:
key(required): The key to get values for (e.g.,$metadata.service,$metadata.level)
Options:
--key-type {string,number,boolean}: Type of the key (default: string)--minutes N: Time range in minutes (default: 60, max: 10080 for 7 days)--limit N: Max values to return (default: 50)--needle PATTERN: Pattern to match values--needle-regex: Treat needle as regex--filter KEY:OP:TYPE:VALUE: Filter (can be repeated)
Example:
uv run scripts/cf_observability_values.py '$metadata.service' --limit 100
cf_observability_query.py
Query the Workers Observability API to analyze logs and metrics from Cloudflare Workers.
Core Capabilities:
This script provides three primary views of your Worker data:
- events (default): Browse individual request logs and errors
- calculations: Compute statistics across requests (avg, p99, etc.)
- invocations: Find specific request invocations matching criteria
Examples by View Type:
Events View:
- "Show all errors for worker llms in the last 30 minutes"
- "Show events where the path contains /api"
Calculation View:
- "What is the p99 wall time for worker llms?"
- "Count requests grouped by status code"
Invocation View:
- "Find a request that resulted in a 500 error"
- "List successful requests with status 200"
Filtering Best Practices:
- Before applying filters, use
cf_observability_keys.pyandcf_observability_values.pyto confirm available fields and values - Common filter fields:
$metadata.service,$metadata.origin,$metadata.trigger,$metadata.message,$metadata.level,$metadata.requestId
Calculation Best Practices:
- Before applying calculations, use
cf_observability_keys.pyto confirm the key exists
Troubleshooting:
- If no results returned, try broadening the time range or relaxing filters
- For errors about invalid fields, use
cf_observability_keys.pyto see available options
uv run scripts/cf_observability_query.py [options]
Options:
--view {events,calculations,invocations}: Query view type (default: events)--minutes N: Time range in minutes (default: 60, max: 10080 for 7 days)--limit N: Max results to return (default: 10)--offset ID: Pagination offset (use$metadata.idfrom previous results)--offset-by N: Numeric offset for pagination--offset-direction {next,prev}: Pagination direction--dry: Dry run - validate query without executing--granularity N: Time bucket granularity for calculations--filter KEY:OP:TYPE:VALUE: Filter (can be repeated)--filter-combination {and,or}: How to combine filters (default: and)--calculation OPERATOR[:KEY[:TYPE[:ALIAS]]]: Calculation (can be repeated, for calculations view)--group-by VALUE[:TYPE]: Field to group by (can be repeated)--order-by ALIAS: Calculation alias to sort by--order {asc,desc}: Sort order (default: desc)--needle TEXT: Full-text search in log content--needle-regex: Treat needle as regex
Filter Format:
Filters use format key:operation:type:value where:
key: Field name (e.g.,$metadata.service)operation: One ofincludes,not_includes,starts_with,regex,exists,is_null,in,not_in,eq,neq,gt,gte,lt,ltetype: One ofstring,number,booleanvalue: Comparison value
Calculation Format:
Calculations use format operator[:key[:key_type[:alias]]] where:
operator: One ofuniq,count,max,min,sum,avg,median,p001,p01,p05,p10,p25,p75,p90,p95,p99,p999,stddev,variancekey: Field to calculate on (optional forcount)key_type: Type of the key (default: number)alias: Name for this calculation in results
Examples:
Show recent errors for the llms worker:
uv run scripts/cf_observability_query.py --filter '$metadata.service:eq:string:llms' --filter '$metadata.level:eq:string:error' --limit 20
Get p99 wall time grouped by service:
uv run scripts/cf_observability_query.py --view calculations --calculation 'p99:wallTime:number:p99_wall' --group-by '$metadata.service'
Count requests by status code:
uv run scripts/cf_observability_query.py --view calculations --calculation 'count' --group-by 'response.status:number'
Search for specific text in logs:
uv run scripts/cf_observability_query.py --needle 'timeout' --minutes 120
cf_analytics_query.py
Query Workers Analytics Engine datasets using the SQL API. This is for custom metrics written via writeDataPoint(), not request logs (use cf_observability_query.py for logs).
Key Features:
- Automatic semantic aliases for known datasets (e.g.,
blob1→path,double1→latency_ms) - Built-in sampling-aware aggregation helpers
- Raw SQL mode for complex queries
Schema for llms_usage dataset:
| Raw Field | Semantic Name | Description |
|---|---|---|
index1 | method | HTTP method or "unauthorized" |
blob1 | path | Request path |
blob2 | status | HTTP status code |
blob3 | request_type | Category: provider, amp-tab, amp-telemetry, amp-admin, management, oauth, other |
blob4 | provider | LLM provider: anthropic, google, openai, etc. (empty for non-provider requests) |
blob5 | model | Model name from path (Gemini only; empty for Anthropic/OpenAI where model is in body) |
blob6 | client | Client identifier: "VS Code CLI", "VS Code Insiders", "Bun", "node", etc. |
double1 | latency_ms | Response time in milliseconds |
double2 | input_tokens | Input/prompt tokens (non-streaming provider requests only; 0 for streaming) |
double3 | output_tokens | Output/completion tokens (non-streaming provider requests only; 0 for streaming) |
uv run scripts/cf_analytics_query.py [options]
Options:
--dataset NAME: Analytics Engine dataset (default: llms_usage)--minutes N: Time range in minutes (default: 60)--limit N: Max results (default: 20)--field FIELD: Field to select (can be repeated). Omit for default fields with aliases.--agg EXPR: Aggregation expression (e.g.,SUM(_sample_interval) AS count). Can be repeated.--group-by FIELD: Field to group by (can be repeated). Use with --agg.--where CONDITION: WHERE clause condition (can be repeated). E.g.,"blob2 = '401'"--order-by FIELD: Field or alias to order by--order {asc,desc}: Sort order (default: desc)--raw QUERY: Execute raw SQL (ignores other query options)--format {json,jsonl,tsv}: Output format (default: json)--show-query: Print generated SQL--show-schema: Show schema mapping for dataset--list-datasets: List available datasets
Examples:
Show recent events with semantic field names:
uv run scripts/cf_analytics_query.py --limit 10
Request counts by path and status (last 24 hours):
uv run scripts/cf_analytics_query.py --agg 'SUM(_sample_interval) AS request_count' --group-by blob1 --group-by blob2 --minutes 1440
Average latency by method:
uv run scripts/cf_analytics_query.py --agg 'SUM(_sample_interval * double1) / SUM(_sample_interval) AS avg_latency_ms' --group-by index1
Filter by status code (show 401 errors):
uv run scripts/cf_analytics_query.py --where "blob2 = '401'" --minutes 1440
Raw SQL query:
uv run scripts/cf_analytics_query.py --raw "SELECT blob1, SUM(_sample_interval) AS count FROM llms_usage GROUP BY blob1 ORDER BY count DESC LIMIT 10"
Sampling Notes:
Analytics Engine may sample high-volume data. Always use _sample_interval for accurate counts:
- Count:
SUM(_sample_interval)instead ofCOUNT() - Sum:
SUM(_sample_interval * field)instead ofSUM(field) - Average:
SUM(_sample_interval * field) / SUM(_sample_interval)instead ofAVG(field)
Preferred Filter Keys
These keys are faster and always available:
$metadata.service: Worker name$metadata.origin: Trigger type (fetch, scheduled, queue, etc.)$metadata.trigger: Request method and path (e.g., GET /users)$metadata.message: Log message text$metadata.error: Error message (when applicable)$metadata.level: Log level (log, warn, error)$metadata.requestId: Unique request identifier
cf_ai_gateway_logs.py
Query AI Gateway logs with conversation-focused interface. Each log entry contains the full conversation history (Anthropic Messages API format), so viewing the latest entry for a conversation gives you everything.
Modes (mutually exclusive, one required):
--conversations: List conversations grouped by conversation-id metadata--conversation ID: Get messages from a specific conversation's latest log--raw: Dump raw logs to /tmp file (prints filename to avoid context overload)
uv run scripts/cf_ai_gateway_logs.py <mode> [options]
Common Options:
--gateway NAME: AI Gateway ID (default: llms)--minutes N: Time range in minutes (default: 60)--limit N: Max results (default: 20)
Options for --conversation mode:
--last-messages N: Only show the last N messages (default: 4, use 0 for all)--include-tools: Include the full tools array (omitted by default)--include-system: Include the full system prompt (omitted by default)--truncate CHARS: Truncate text content to N characters
Options for --raw mode:
--include-bodies: Include request bodies in dump (slow, fetches each individually)
Examples:
List recent conversations:
uv run scripts/cf_ai_gateway_logs.py --conversations --limit 10
Get last 10 messages from a conversation:
uv run scripts/cf_ai_gateway_logs.py --conversation T-xxx-xxx --last-messages 10
Dump 100 raw logs to file:
uv run scripts/cf_ai_gateway_logs.py --raw --limit 100
Include request bodies in raw dump:
uv run scripts/cf_ai_gateway_logs.py --raw --limit 10 --include-bodies
Workflow Example:
- List conversations:
uv run scripts/cf_ai_gateway_logs.py --conversations - Pick a conversation ID from the output
- View messages:
uv run scripts/cf_ai_gateway_logs.py --conversation T-xxx --last-messages 10
Regex Notes
For regex operations, Cloudflare uses ClickHouse RE2 syntax (not PCRE/JavaScript):
- No lookaheads/lookbehinds
- Escape backslashes with double backslash