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otel-ottl

Skill99 starsChanged 13 days agoApache-2.0View on GitHub

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.

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    1. ollygarden/opentelemetry-agent-skills★ 125same name

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository4 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

6 rules. About 0 are common, 1 is distinctive, and 5 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 5

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use int64 constants for enumeration fields:

    line 33
  2. Very specific:

    Use where to apply transformations conditionally:

    line 67
  3. Very specific:

    Use nil for absence checking (not null):

    line 76
  4. Very specific:

    Always set error_mode explicitly.

    line 136
  5. Very specific:

    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 …

    line 156
  6. Very specific:

    Use where clauses to skip items early.

    line 160

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

OpenTelemetry Transformation Language (OTTL)

Components that use OTTL

OTTL is not limited to the transform and filter processors. Processors (transform, filter, tailsampling, logdedup) and connectors (routing, count, sum, signaltometrics) accept OTTL expressions. See components for the full list with use cases.

OTTL syntax

Path expressions

Navigate telemetry data using dot notation:

span.name
span.attributes["http.method"]
resource.attributes["service.name"]

Contexts (first path segment): resource, scope, span, spanevent, metric, datapoint, log.

Enumerations

Use int64 constants for enumeration fields:

span.status.code == STATUS_CODE_ERROR
span.kind == SPAN_KIND_SERVER

Operators

Assignment: = — Comparison: ==, !=, >, <, >=, <= — Logical: and, or, not

Functions

Converters (uppercase, return values):

ToUpperCase(span.attributes["http.request.method"])
Substring(log.body.string, 0, 1024)
Concat(["prefix", span.attributes["request.id"]], "-")
IsMatch(metric.name, "^k8s\\..*$")

Editors (lowercase, modify data in-place):

set(span.attributes["region"], "us-east-1")
delete_key(resource.attributes, "internal.key")
limit(log.attributes, 10, [])

See function-reference for the full list of editors and converters.

Conditional statements

Use where to apply transformations conditionally:

<!-- eval:skip -->
span.attributes["db.statement"] = "REDACTED" where resource.attributes["service.name"] == "accounting"

Nil checks

Use nil for absence checking (not null):

resource.attributes["service.name"] != nil

Validation workflow

  1. Validate config syntax — run otelcol validate --config=config.yaml to catch compilation errors before starting the Collector.
  2. Test with the debug exporter — route transformed telemetry to a debug exporter and inspect the output:
exporters:
  debug:
    verbosity: detailed

service:
  pipelines:
    traces:
      receivers: [otlp]
      processors: [transform]
      exporters: [debug]   # swap in production exporter once validated
  1. Set error_mode: ignore in production — see Error handling.
  2. Promote to production exporters — replace debug with the production exporter.

Common patterns

<!-- keep-in-sync: each entry must match a ## heading in ./rules/patterns.md -->
  • Set attributes
  • Drop telemetry by pattern
  • Drop stale data
  • Backfill missing timestamps
  • Filter processor example
  • Transform processor example
  • Defensive nil checks
  • Redact sensitive data — strategies: replace, mask, hash, delete, and drop.
  • Normalize high-cardinality attributes — path segments, IP masking, and attribute count/length limits.
  • Enrich telemetry with static attributes

Error handling

Compilation errors

Occur during processor initialization and prevent Collector startup:

  • Invalid syntax (missing quotes)
  • Unknown functions
  • Invalid path expressions
  • Type mismatches

Runtime errors

Occur during telemetry processing:

  • Accessing non-existent attributes
  • Type conversion failures
  • Function execution errors

Error mode configuration

Always set error_mode explicitly; the default differs by component. The transform and filter processors default to ignore since Collector Contrib v0.153.0 and to propagate before it. The routing and signaltometrics connectors default to propagate. The count and sum connectors have no error_mode key and always propagate errors.

ModeBehaviorWhen to use
ignoreLogs the error and continues to the next statementProduction and general use — the default for the transform and filter processors
propagateReturns the error up the pipeline, dropping the payload from the CollectorDevelopment and strict environments where you want to catch every error
silentIgnores errors without loggingHigh-volume pipelines with known-safe transforms where error logs are noise
processors:
  transform:
    error_mode: ignore
    trace_statements:
      - set(span.attributes["parsed"], ParseJSON(span.attributes["json_body"]))

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.

Performance

Use where clauses to skip items early.

# 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

References

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