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デザイン · SKILL.md

tracing-observability

tracing-observability

Configure OpenAI Agents Python tracing, trace processors, spans, sensitive-data controls, logging, usage tracking, and agent visualization.

Independent GitHub snapshot · Automated classification · Original documentation governs

スキルの説明

GitHub

name: tracing-observability description: "Configure OpenAI Agents Python tracing, trace processors, spans, sensitive-data controls, logging, usage tracking, and agent visualization." disable-model-invocation: true metadata: disco-role: operating license: MIT

Tracing & Observability

Use this sub-skill when a task mentions tracing, trace_include_sensitive_data, workflow_name, trace_id, group_id, trace_metadata, Span, trace processors, usage, debug logs, visualization, Graphviz, or a tracing/export API key.

Start Here

  • Read references/tracing-reference.md for verified tracing APIs, config fields, processors, spans, sensitive-data controls, usage, logging, and visualization surfaces.
  • Use references/workflows.md for implementation patterns: enable/disable tracing, custom processors, trace metadata, usage collection, visualization generation, and safe logging.
  • Use references/troubleshooting.md for missing trace API keys, disabled tracing, sensitive payload leakage, processor/exporter failures, flush/shutdown behavior, and Graphviz optional dependency issues.
  • Run scripts/check_tracing_config.py for a safe no-network import/config check that masks secret values and can emit JSON.

Routing Boundaries

  • Stay here for RunConfig.tracing_disabled, RunConfig.tracing, RunConfig.trace_include_sensitive_data, workflow_name, trace_id, group_id, trace_metadata, trace(), span helpers, TracingProcessor, add_trace_processor(), set_trace_processors(), flush_traces(), Usage, SDK loggers, and draw_graph().
  • Route model/provider API key selection, OpenAI-compatible endpoints, Responses websocket transport, and adapter-specific model setup to ../models-providers/SKILL.md.
  • Route core Runner call shapes, RunResult, streaming event interpretation, sessions, and RunState resume mechanics to ../core-runtime/SKILL.md.
  • Route realtime and voice-specific tracing controls, including audio payload controls, to ../realtime-voice/SKILL.md.

Fast Decisions

  • Tracing is enabled by default; disable it globally with OPENAI_AGENTS_DISABLE_TRACING=1 or set_tracing_disabled(True), and per run with RunConfig(tracing_disabled=True).
  • Set a logical workflow_name for every production workflow and use group_id to link traces from one conversation or job family.
  • Set trace_include_sensitive_data=False for sensitive workloads; it redacts model/tool trace payloads but does not automatically sanitize application exceptions, logs, metadata, or custom processor output.
  • Use add_trace_processor() to observe traces in addition to the default OpenAI exporter; use set_trace_processors() only when intentionally replacing default export behavior.
  • Call flush_traces() after a trace context closes when a short-lived job or background task needs immediate export delivery.
  • Use result.context_wrapper.usage for token/request accounting and draw_graph() for local topology visualization when the optional Graphviz package is available.

Safety Notes

  • Never print API key values, per-run tracing={"api_key": ...} values, or local machine paths in diagnostics.
  • Keep custom processors non-blocking and defensive; processor/exporter exceptions are logged as non-fatal but can drop observability data.
  • Treat verbose logs and exception chains as separate leakage channels from tracing payload controls.
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