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Errors

Every ArcFlow error has 5 fields: class, code, message, failing_field, and recovery_suggestion. Agents can parse class + code to decide recovery strategy without reading the message.

TypedError {
    class: ErrorClass                    // category for routing
    code: String                         // e.g., "INVALID_LABEL"
    message: String                      // human-readable
    failing_field: String?               // which input was wrong
    recovery_suggestion: String?         // what to do about it
}

Error Classes#

ClassMeaningWhose fault
ValidationInput validation failureCaller
IntegrationInternal engine bug or misconfigurationEngine
ArchitectureArchitectural constraint violationDesign
TimeoutOperation timed outEnvironment

Error Codes#

CodeCategoryCauseFix
EXPECTED_KEYWORDparseQuery syntax errorCheck MATCH / CREATE / MERGE syntax
UNEXPECTED_TOKENparseUnexpected token in queryCheck clause order and punctuation
UNKNOWN_FUNCTIONvalidationFunction name not recognisedRun CALL db.help() for full list
UNKNOWN_PROCEDUREvalidationCALL target not foundRun CALL db.procedures()
UNKNOWN_LABELvalidationLabel doesn't exist in schemaCheck CALL db.schema()
INVALID_PARAMETERvalidationParameter type mismatchEnsure param types match QueryParams
MISSING_PARAMETERvalidation$param used but not suppliedPass all parameters in the params object
DB_CLOSEDintegrationQuery after db.close()Don't query a closed database
LOCK_POISONEDintegrationWrite lock poisoned by panicRestart the database process
COMPILE_ERRparseQuery failed to compileCheck query against GQL reference
VECTOR_DIM_MISMATCHvalidationQuery vector ≠ index dimensionsMatch vector length to OPTIONS {dimensions}
INDEX_NOT_FOUNDvalidationNamed index doesn't existCheck CALL db.indexes
CONSTRAINT_VIOLATIONvalidationUnique constraint failedUse MERGE instead of CREATE
WORKFLOW_NOT_FOUNDvalidationarcflow.workflow.* target not foundRun CALL arcflow.workflow.list
STEP_NOT_FOUNDvalidationStep name not in workflowCheck step name spelling
EXECUTION_CONTEXT_MISMATCHintegrationrequireExecutionContext guard failedCALL db.setExecutionContext(...) first
UNKNOWN_EXECUTION_CONTEXTvalidationInvalid context stringUse local_cpu, local_gpu, or distributed
TEMPORAL_WAL_NOT_WIREDintegrationAS OF seq N without WAL contextOpen the store with WAL enabled (open() or openInMemory() with sync options)

Design Principle#

Every error is fail-fast and typed. No generic "something went wrong." Agents can parse class + code to decide recovery strategy without reading the message field.

AIOps Telemetry (opt-in)#

ArcFlow can optionally send error and performance telemetry to OZ's AIOps observability unit. This is off by default. When enabled, the engine streams structured error events and performance signals to aiops.oz.com over an encrypted channel.

Why opt in? Every error that reaches OZ gets processed by an automated diagnostics pipeline. Patterns across deployments surface issues that no single operator would catch: a GPU memory pressure trend that precedes failures, a query pattern that degrades under specific graph shapes, a clock drift that corrupts temporal indexes. The more engines report, the faster ArcFlow gets for everyone.

What gets sent#

  • TypedError events (class, code, failing_field; never query content or graph data)
  • Performance counters: query latency percentiles, GPU utilization, memory pressure, WAL write throughput
  • Engine metadata: version, deployment type (native, Docker, PanoNode, browser), OS, GPU model

No graph data, no query strings, no user content. The telemetry payload is structural, not semantic.

Enabling telemetry#

# Enable in CLI
arcflow --telemetry on
 
# Or set in config
arcflow config set telemetry.enabled true

Telemetry flows through the same sync channel that ArcFlow Cloud uses for fragment coordination. If your engine is already connected to ArcFlow Cloud, telemetry rides the existing connection. If not, it opens a dedicated encrypted channel to aiops.oz.com.

How it helps you#

OZ's AIOps team monitors telemetry across the fleet continuously. If your engine hits a pattern that's been seen (and solved) elsewhere, you benefit from that fix faster. If your deployment surfaces a new edge case, the engineering team sees it before it becomes a problem. You're not debugging alone.

You can disable telemetry at any time. The engine runs identically with or without it.


See Also#

  • Error Handling — structured errors with machine-readable codes and recovery hints
  • TypeScript API Reference — db.query() and db.mutate() error surfaces
  • ArcFlow for Coding Agents — how agents pattern-match on error codes and self-correct
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