axiomhq/cli/find-traces

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Analyze OpenTelemetry distributed traces from Axiom. Use when investigating a trace ID, finding traces by criteria (errors, latency, service), or debugging distributed system issues.

Install

npx vskill@latest install axiomhq/cli/find-traces

SKILL.md

Trace Analysis

Analyze OpenTelemetry distributed traces to identify errors, latency issues, and root causes.

Arguments

When invoked with a trace ID (e.g., /find-traces abc123...), it's available as $ARGUMENTS.

Trace Dataset Discovery

First, find trace datasets:

bash
axiom dataset list -f json

Look for datasets containing trace data (often named *traces*, *spans*, or otel-*).

Schema Discovery

Always verify field names first:

bash
axiom query "['<trace-dataset>'] | getschema" --start-time -1h

Common Operations

Get Trace by ID
bash
axiom query "['<dataset>']
| where trace_id == '<TRACE_ID>'
| sort by _time asc
| limit 100" --start-time -1h -f json
Find Error Traces
bash
axiom query "['<dataset>']
| where _time >= ago(1h)
| where error == true
| extend error = coalesce(ensure_field(\"error\", typeof(bool)), false)
| summarize
start_time = min(_time),
total_duration = max(duration),
span_count = count(),
error_count = countif(error),
services = make_set(['service.name']),
root_operation = arg_min(_time, name)
by trace_id
| sort by start_time desc
| limit 20" --start-time -1h -f json
Find Slow Traces
bash
axiom query "['<dataset>']
| where _time >= ago(1h)
| where duration >= 1000000000
| summarize
start_time = min(_time),
total_duration = max(duration),
span_count = count(),
services = make_set(['service.name'])
by trace_id
| sort by total_duration desc
| limit 20" --start-time -1h -f json
Find Traces by Service
bash
axiom query "['<dataset>']
| where _time >= ago(1h)
| where ['service.name'] == '<SERVICE>'
| summarize
start_time = min(_time),
total_duration = max(duration),
span_count = count(),
error_count = countif(error == true)
by trace_id
| sort by start_time desc
| limit 20" --start-time -1h -f json
Error Spans in Trace
bash
axiom query "['<dataset>']
| where trace_id == '<TRACE_ID>'
| where error == true
| project _time, ['service.name'], name, duration, ['status.message']" --start-time -1h -f json
Critical Path Analysis
bash
axiom query "['<dataset>']
| where trace_id == '<TRACE_ID>'
| project span_id, parent_span_id, ['service.name'], name, duration, error
| sort by duration desc" --start-time -1h -f json

OTel Field Reference

FieldBracket?Description
trace_idNo32-char trace identifier
span_idNo16-char span identifier
parent_span_idNoParent span (empty for root)
nameNoOperation name
durationNoDuration in nanoseconds
kindNoCLIENT, SERVER, INTERNAL, PRODUCER, CONSUMER
errorNoBoolean error flag
['service.name']YesService identifier
['status.code']YesOK, ERROR, or nil
['status.message']YesError description
['scope.name']YesInstrumentation library

Duration Conversion

OTel durations are in nanoseconds:

HumanNanosecondsFilter
1 ms1,000,000duration >= 1000000
100 ms100,000,000duration >= 100000000
1 s1,000,000,000duration >= 1000000000

Convert for display:

apl
| extend duration_ms = duration / 1000000.0

Custom Attributes

Non-standard span attributes are stored in attributes.custom map:

apl
// Filter by custom attribute
| where ['attributes.custom']['user_id'] == "123"
// Aggregation requires explicit cast
| summarize count() by tostring(['attributes.custom']['tenant'])

Without tostring(), aggregations fail with "grouping by field of type unknown".

Codebase Correlation

When working in a repository that matches the traced service, correlate trace data with source code to identify root causes.

Mapping Trace Data to Code
  1. Extract package/module path from `['scope.name']`
  • Contains the instrumentation library or package path
  • Strip the module prefix to get the local path
  • Example: github.com/org/repo/pkg/auth → pkg/auth
  1. Find code from operation name
  • The name field often contains function names or HTTP routes
  • Search the codebase for matching handlers, functions, or endpoints
  1. Trace the call chain
  • Follow parent-child span relationships
  • Map each span to its corresponding code location
  • Identify where errors originate and propagate

Note: Codebase correlation is optional. Proceed with trace-only analysis if code is unavailable or doesn't match the traced services.

Output Format

When analyzing a trace, provide:

markdown
## Trace Summary
-**Trace ID:** <id>
-**Duration:** <human-readable>
-**Services:** <list>
-**Outcome:** success/failure
## Sequence of Events
1.<Service> - <operation> (<duration>)
2.<Service> - <operation> (<duration>) ⚠️ ERROR
...
## Error Analysis
<What failed, when, why>
## Root Cause
<Deepest error and explanation>
## Codebase Locations (if applicable)
-**Service:** <service.name>
-**Package:** <scope.name>
-**Files:** <specific files to investigate>
## Recommended Actions
1.<Specific action>
2.<What to investigate next>

When NOT to Use

  • Metrics analysis: Traces are for request flow; use logs/metrics skills for aggregated performance data
  • Non-OTel data: This skill assumes OpenTelemetry field conventions (trace_id, span_id, etc.)
  • Known trace structure: If you already have the query, run it directly without invoking this skill
  • Alerting on trace patterns: Use Axiom Monitors for continuous alerting

APL Reference

For query syntax, invoke the axiom-apl skill which provides trace analysis patterns and duration unit guidance.

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
58
Repository forks
12
7-day trend score
20

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 26 Apr 2026, 6 months ago.

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