npx skills add ...
npx skills add dash0hq/agent-skills --skill otel-ottl
npx skills add dash0hq/agent-skills --skill otel-ottl
OpenTelemetry Transformation Language (OTTL) expert. Use when writing or debugging OTTL expressions for any OpenTelemetry Collector component that supports OTTL (processors, connectors, receivers, exporters). Triggers on tasks involving telemetry transformation, filtering, attribute manipulation, data redaction, sampling policies, routing, or Collector configuration. Covers syntax, contexts, functions, error handling, and performance.
OTTL is not limited to the transform and filter processors. Processors (transform, filter, attributes, span, tailsampling, cumulativetodelta, logdedup, lookup), connectors (routing, count, sum, signaltometrics), and the hostmetrics receiver all accept OTTL expressions. See components for the full list with use cases.
Navigate telemetry data using dot notation:
Contexts (first path segment): resource, scope, span, spanevent, metric, datapoint, log.
Use int64 constants for enumeration fields:
Assignment: = — Comparison: ==, !=, >, <, >=, <= — Logical: and, or, not
Converters (uppercase, return values):
Editors (lowercase, modify data in-place):
See function-reference for the full list of editors and converters.
Use where to apply transformations conditionally:
Use nil for absence checking (not null):
otelcol validate --config=config.yaml to catch compilation errors before starting the Collector.debug exporter and inspect the output:error_mode: ignore in production — see Error handling.debug with the production exporter.Occur during processor initialization and prevent Collector startup:
Occur during telemetry processing:
Set error_mode explicitly for clarity; ignore is the default.
| Mode | Behavior | When to use |
|---|---|---|
ignore (default) | Logs the error and continues to the next statement | Production and general use — the default for the transform and filter processors |
propagate | Returns the error up the pipeline, dropping the payload from the Collector | Development and strict environments where you want to catch every error |
silent | Ignores errors without logging | High-volume pipelines with known-safe transforms where error logs are noise |
Statements are a flat list; the Collector infers the context (span, metric, datapoint, log, and so on) from the path prefixes.
Use the object form with an explicit context: only when a statement group mixes paths that cannot be inferred to a single context, or when you need a group-level condition or error_mode.
Use where clauses to skip items early.
exporters:
debug:
verbosity: detailed
service:
pipelines:
traces:
receivers: [otlp]
processors: [transform]
exporters: [debug] # swap in production exporter once validatedprocessors:
transform:
error_mode: ignore
trace_statements:
- set(span.attributes["parsed"], ParseJSON(span.attributes["json_body"]))# BAD — runs replace_pattern on every span
replace_pattern(span.attributes["url.path"], "/\\d+", "/{id}")
# GOOD — skips spans that lack the attribute
replace_pattern(span.attributes["url.path"], "/\\d+", "/{id}") where span.attributes["url.path"] != nil