{"categories":[{"label":"Monitoring","url":"https://skillfed.io/packages/category/system-monitoring/3"}],"enrichment":{"capability":"Automatically captures and exports traces from Anthropic API calls to OpenTelemetry-compatible collectors like Arize Phoenix, enabling observability of LLM interactions.","skillfed_tags":["llm-observability","opentelemetry","anthropic-integration"],"use_cases":["Debug Anthropic API calls in development by viewing detailed traces and attributes.","Monitor production LLM application performance and identify slow or failing Anthropic requests.","Track token usage and cost across Anthropic API calls for billing and optimization.","Analyze conversation patterns and model behavior across multiple Anthropic client instances.","Correlate Anthropic traces with other application metrics in a unified observability platform."],"what_it_does":"This package wraps Anthropic's Python client to automatically capture detailed traces of all API calls\u2014including Messages, Completions, and their async variants\u2014and exports them to any OpenTelemetry-compatible backend. It sits between your code and the Anthropic client, intercepting requests and responses without requiring code changes beyond a single instrumentation call.\n\nThe traces include request parameters, response data, and execution timing, formatted according to OpenInference conventions so they integrate seamlessly with observability platforms. It's designed for developers building LLM applications who need visibility into what their Anthropic calls are doing\u2014latency, token usage, errors, and behavior patterns\u2014without manually logging each interaction.","worth_installing":"Yes. The package is actively maintained, has no known vulnerabilities, installs with low friction, and solves a real observability gap for Anthropic users. If you're already using or considering OpenTelemetry and an OTLP-compatible collector, this is a straightforward way to gain visibility into LLM interactions."},"id":"openinference-instrumentation-anthropic","links":{"html":"https://skillfed.io/packages/openinference-instrumentation-anthropic","md":"https://skillfed.io/packages/openinference-instrumentation-anthropic.md","pypi":"https://pypi.org/project/openinference-instrumentation-anthropic/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-07","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"openinference-instrumentation-anthropic","python_support":"supports_current","summary":"OpenInference Anthropic Instrumentation"},"popularity":{"monthly_downloads":651145,"position":5553,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.1.2"}