langfuse-trace-loggerLog subagent task completions as Langfuse traces for replay, evaluation, and cost analysis. Called during session-wrap Phase 4. Supports backfill, tag-based...
Install via ClawdBot CLI:
clawdbot install nissan/langfuse-trace-loggerGrade Limited — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
http://localhost:3100Audited Apr 17, 2026 · audit v1.0
Generated Apr 20, 2026
A customer support platform uses this skill to log traces of AI agents handling support tickets, enabling replay and evaluation of responses for quality assurance and training. It helps analyze cost efficiency by comparing different AI models like Claude Sonnet vs. Haiku for similar tasks, optimizing resource allocation.
A marketing agency employs the skill to trace AI subagents generating blog posts or social media content, logging inputs, outputs, and token usage. This allows for replaying tasks with cheaper models to reduce costs while maintaining quality, and filtering by project or skill to assess effectiveness.
A tech company integrates the skill to log AI agents performing code reviews or debugging tasks, capturing prompts and results for replay and evaluation. It supports backfilling historical data from memory files to analyze trends and improve agent routing decisions based on duration and token metrics.
A healthcare provider uses the skill to trace AI subagents assisting with diagnostic queries, logging task completions for replay and judge runs to compare model accuracy. Tag-based filtering enables analysis by agent or status, ensuring compliance and data stays on-premise with self-hosted Langfuse.
An e-commerce platform leverages the skill to log AI agents creating product descriptions, with traces used for cost analysis by comparing token usage across models. Backfill capabilities allow retroactive logging from memory files to fill gaps and enable project-level reporting for inventory management.
Offer a cloud-based service where users subscribe to access Langfuse trace analytics, with tiered pricing based on trace volume and features like replay-judge integration. Revenue comes from monthly fees, targeting businesses using AI agents for operational tasks.
Provide consulting to help companies integrate this skill into their AI workflows, including setup, backfill, and custom replay-judge configurations. Revenue is generated through project-based fees and ongoing support contracts, focusing on industries like customer service or marketing.
Sell licenses for self-hosted Langfuse instances bundled with this skill, catering to organizations with strict data privacy needs. Revenue includes one-time license fees and optional maintenance packages, ideal for healthcare or finance sectors requiring local data storage.
💬 Integration Tip
Ensure Python 3.11 is used via chatterbox-venv to avoid silent failures, and set LANGFUSE_PUBLIC_KEY and LANGFUSE_SECRET_KEY environment variables for proper trace logging.
Scored Apr 20, 2026
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