Instrument Python agents with HiveLoop to stream telemetry to HiveBoard.
npx skills add https://github.com/jcolano/loopColony --skill integrate-hiveloop
Please help me install this Agent Skill. Skill: integrate-hiveloop Source: https://github.com/jcolano/loopColony/tree/main/.claude/skills/integrate-hiveloop Command: npx skills add https://github.com/jcolano/loopColony --skill integrate-hiveloop
Agentic applications often lack structured observability for agent identity, task lifecycle, LLM usage, costs, and errors; this Skill guides integrating the HiveLoop SDK to capture and stream those telemetry events to HiveBoard for actionable monitoring and troubleshooting.
Initialize hiveloop with your API key at process startup, register each agent with hb.agent, wrap each work unit with agent.task, record LLM responses with task.llm_call, and call hiveloop.shutdown on exit.
High-intent search queries and answers about installing and using this skill.
To add observability to Python agent applications, integrate the HiveLoop SDK to capture and stream telemetry, task lifecycle events, and LLM call metrics to HiveBoard. Initialize hiveloop at startup, register agents, wrap work units with agent.task, and record LLM responses with task.llm_call.
The proper initialization sequence for HiveLoop telemetry requires running hiveloop.init at process startup before any agent registration occurs. This ensures telemetry is available from the first agent action and allows you to attach identity, framework, and heartbeat state via hb.agent.
You track LLM token usage and latency in Python pipelines by recording calls via task.llm_call or agent.llm_call. This captures token counts, latency, and cost data to power cost and latency dashboards within HiveBoard for actionable monitoring.
Yes, you can use HiveLoop to monitor LangChain agents and sales lead scoring pipelines. The SDK applies to Python agentic applications and frameworks, allowing you to see per-task LLM costs, action trees, and error trends in HiveBoard.
To ensure graceful shutdown and capture agent errors with HiveLoop, invoke hiveloop.shutdown on process exit and optionally add HiveBoardLogHandler. This forwards warnings and errors as issues to HiveBoard, ensuring telemetry streams are properly flushed and closed.
HiveLoop telemetry fails to capture first agent actions if hiveloop.init does not run before agent registration. Ensure hiveloop.init executes at process startup so telemetry is available from the very first agent action, preventing missed lifecycle events.
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