Neotask övervakar dina AI-agenter med AgentOps - Neotask-agenter analyserar sessioner, spårar prestanda och identifierar problem i dina AI-arbetsflöden.
Övervaka agentsessioner, spåra händelser och analysera prestanda genom konversation
Identifiera felsökningsproblem, flaskhalsar och avvikelser i agentbeteende automatiskt
Generera insiktsrapporter, jämför agentkörningar och optimera AI-arbetsflöden
Vad du kan göra
The AgentOps integration gives Neotask 6 observability actions across two server variants - a remote Node.js server for trace/span retrieval and a local Python server for session listing and detail views.
Spårningshantering
get_trace - fetch a complete trace by ID, including timing, model calls, and tool invocations
get_complete_trace - retrieve the full trace tree with all nested spans for deep inspection
get_span - drill into a specific span within a trace for granular timing and payload data
Sessionslista
list_traces - enumerate recent agent sessions filterable by status, model, and time range
trace_detail - pull a detailed breakdown of a specific session including error context
Autentisering
auth - authenticate with your AgentOps workspace before querying trace data
Varje åtgärd körs autonomt eller kräver ditt godkännande - du bestämmer.
Prova att fråga
"What traces failed in the last 24 hours? Show me the error messages"
"Pull the complete trace for session abc123 - I need to see every span"
"List all agent sessions from yesterday that took more than 30 seconds"
"Get me the span details for the tool call that timed out in trace xyz789"
"Which sessions had the highest token usage this week?"
Proffstips
Pair AgentOps with your alerting integration so your agent automatically pages you when error rates spike above a threshold
Schedule a daily trace audit: your agent reviews failures from the previous day and summarizes patterns before your morning standup
Use approval gates when pulling large trace payloads - review before storing them in external systems
For multi-agent teams, use AgentOps traces to verify that your orchestration logic is working as designed, not just that individual agents completed
Multiple workspaces and capacity for larger teams.
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