civitai Axiom
Query Axiom datasets using APL (Axiom Processing Language). Supports log search, aggregation, field analysis, and time-based filtering.
Setup
Create .env in this skill directory:
AXIOM_TOKEN=xaat-your-token-here
AXIOM_ORG_ID=your-org-id
AXIOM_DATASTREAM=civitai-prod
AXIOM_DOMAIN=api.axiom.co
Token needs read/query permissions (the project .env token is ingest-only).
Quick Reference
SKILL_DIR=".claude/skills/axiom"
# List available datasets
node "$SKILL_DIR/axiom.mjs" datasets
# Run an APL query
node "$SKILL_DIR/axiom.mjs" query "['civitai-prod'] | where name == 'nowpayments-webhook' | take 10" --format legacy --json
# Search logs with filters
node "$SKILL_DIR/axiom.mjs" query "['civitai-prod'] | where name == 'some-service' and type == 'error' | project _time, message, error | sort by _time desc | take 50" --start "2026-03-01T00:00:00Z" --end "2026-04-01T00:00:00Z" --format legacy --json
# Count errors by message
node "$SKILL_DIR/axiom.mjs" query "['civitai-prod'] | where name == 'my-service' | summarize count() by message | order by count_ desc" --start "2026-03-01T00:00:00Z" --format legacy --json
# Top values for a field
node "$SKILL_DIR/axiom.mjs" query "['civitai-prod'] | where type == 'error' | summarize count() by name | order by count_ desc | take 20" --format legacy --json
Commands
| Command | Description |
|---|---|
datasets |
List all available datasets |
dataset-info <name> |
Get info about a specific dataset |
query "<APL>" |
Run any APL query |
search <dataset> --where "..." |
Search with filters |
count <dataset> --where "..." --by <field> |
Count/aggregate |
tail <dataset> |
Most recent events |
top <dataset> <field> |
Top values for a field |
Important Notes
- Use
--format legacy --jsonfor reliable output. The tabular format can return empty rows for some queries. - Time ranges: Use
--startand--endflags with ISO 8601 timestamps, or useago()in APL (e.g.,_time > ago(24h)). - Field paths: Log data is under the
data.prefix in legacy format. Use field names directly in APL (e.g.,name,message,type). - Summarize queries: Return results in
buckets.series[].groups[]in legacy format, not inmatches[].
Known Datasets
| Dataset | Description |
|---|---|
civitai-prod |
Main production logs (services, webhooks, jobs) |
civitai-stage-new |
Staging environment |
civitai-next |
Next.js application logs |
webhooks |
Webhook event tracking |
clickhouse |
ClickHouse integration errors |
notifications |
Notification service logs |
orchestration-otlp |
Orchestration telemetry |
python-worker |
Python worker process logs |
Common Log Names (civitai-prod)
Services log with a name field. Common ones:
nowpayments-webhook— NowPayments IPN webhook handlernowpayments-service— NowPayments deposit processingreconcile-nowpayments-job— Reconciliation cron job
APL Cheatsheet
# Filter
| where name == "value"
| where field contains "substring"
| where field matches regex "pattern"
# Time range
| where _time > ago(7d)
| where _time between (datetime(2026-03-01) .. datetime(2026-03-31))
# Aggregate
| summarize count() by field
| summarize avg(duration), max(duration) by name
| summarize count() by bin(_time, 1h)
# Sort and limit
| sort by _time desc
| take 50
| order by count_ desc
# Select fields
| project _time, name, message, error
# Extend (computed columns)
| extend duration_ms = duration / 1000
When to Use
- Investigating production errors or webhook failures
- Checking if a specific service is logging errors
- Analyzing error patterns over time
- Debugging payment/deposit processing issues
- Monitoring reconciliation job health
- Verifying deployment behavior changes