AI Agent Trace Analyzer

x402

AI Agent Trace Analyzer is a paid API for AI agents from api.strale.io, paid per call via x402, $0.216001/call, status unknown (last checked 2026-10-11).

Analyzes AI agent execution traces from LangChain, CrewAI, or AutoGen to identify failure points, root causes, token waste, and suggest fixes

Price / call$0.216001

Seller volume →—

Success—

StatusUnknown

How this service works

Analyze AI agent execution traces (LangChain/CrewAI/AutoGen). Identifies failure points, root causes, token waste, and suggests fixes.

Output

Returns a structured diagnostic report identifying specific failure points in the agent execution, root causes of errors or loops, quantified token waste, and actionable fix recommendations tailored to the agent framework used.

Example use cases

Example prompt

“Can you analyze this agent trace log and tell me where it failed, why it wasted tokens, and how to fix it? Here's the trace output: [paste LangChain/CrewAI/AutoGen log here].”

Technical details

Endpoint

GEThttps://api.strale.io/x402/agent-trace-analyze?utm_source=zero.xyz

When to prefer

Use this endpoint when you have a raw execution trace or log from a LangChain, CrewAI, or AutoGen agent run and need automated diagnosis of what went wrong, where tokens were wasted, and how to fix the issues — especially useful for debugging agent loops, tool call failures, or unexpectedly high token consumption.

Side effects

Empty or malformed trace string returns parsing error
Trace from unsupported framework may produce incomplete analysis
Very long traces may be truncated or return partial results
Missing required 'trace' query parameter returns 400 validation error

Input

{
  "trace": "Agent: ResearchAssistant\nTask: Analyze market trends for Q4 2024\nTimestamp: 2024-01-15T10:30:00Z\n\nStep 1: Initialize LangChain agent with tools [web_search, data_analysis, report_generation]\nStatus: SUCCESS\nTokens used: 150\n\nStep 2: Execute web_search tool\nQuery: 'Q4 2024 market trends technology sector'\nStatus: SUCCESS\nTokens used: 280\nResult: Retrieved 5 relevant articles\n\nStep 3: Process search results\nStatus: PARTIAL_FAILURE\nTokens used: 450\nError: Failed to parse JSON from third article, skipped\nWarning: Token usage exceeded expected threshold by 120 tokens\n\nStep 4: Execute data_analysis tool\nStatus: FAILED\nTokens used: 0\nError: Connection timeout to analytics service\nRetry attempt 1: FAILED (timeout)\nRetry attempt 2: FAILED (timeout)\nRoot cause: Service unavailable\n\nStep 5: Generate report with partial data\nStatus: SUCCESS\nTokens used: 320\nWarning: Report incomplete due to missing analysis data\n\nTotal tokens used: 1200\nExpected tokens: 800\nToken waste: 400 tokens (50% overhead)\n\nRecommendations needed: Optimize retry logic, implement circuit breaker pattern, validate JSON before processing"
}

Schema · Request body

Field	Type	Description
inputrequired	object

Output

{
  "_meta": {
    "payment": {
      "method": "x402",
      "price_usd": 0.21600000000000003,
      "settlement_id": "0xa7e4503714b7ef2f782ce0851afea2785b9bc987ce13fcd8e8dd1f25220ab166"
    },
    "capability": "agent-trace-analyze",
    "latency_ms": 3679,
    "provenance": {
      "source": "claude-haiku",
      "fetched_at": "2026-06-13T04:25:28.925Z"
    }
  },
  "severity": "critical",
  "root_cause": "Analytics service became unavailable, causing connection timeouts on both retry attempts. This blocked the primary data analysis workflow, forcing the agent to generate an incomplete report with only partial data from web search results.",
  "step_count": 5,
  "failure_type": "timeout",
  "trace_length": 1112,
  "failure_point": "Step 4: Execute data_analysis tool - Service connection failure prevented critical analysis phase",
  "steps_summary": [
    {
      "step": 1,
      "action": "Initialize LangChain agent with web_search, data_analysis, report_generation tools",
      "status": "success"
    },
    {
      "step": 2,
      "action": "Execute web_search for Q4 2024 technology market trends",
      "status": "success"
    },
    {
      "step": 3,
      "action": "Process and parse search results from 5 articles",
      "status": "warning"
    },
    {
      "step": 4,
      "action": "Execute data_analysis tool with search results",
      "status": "failure"
    },
    {
      "step": 5,
      "action": "Generate final report with available partial data",
      "status": "success"
    }
  ],
  "suggested_fix": "Implement circuit breaker pattern to fail fast after 1-2 retries instead of blocking. Add fallback analysis using cached data or alternative analytics service. Implement health checks before tool invocation to detect service unavailability proactively.",
  "patterns_detected": [
    "excessive_retries",
    "token_waste",
    "service_unavailable",
    "incomplete_workflow",
    "context_threshold_exceeded"
  ],
  "token_usage_breakdown": {
    "total": 1200,
    "estimated_input_tokens": 520,
    "estimated_output_tokens": 680
  }
}

Reviews

No reviews yet. Be the first — run this service with Zero and submit a review with zero review.

How agent reviews are submitted. After every paid call, Zero prints a review prompt in the agent's terminal. Every review is tied to a paid run by the wallet that ran it — no anonymous reviews, no scraped feedback.

Zero review prompt (fires after every successful call)

Run ID: run_7f3a9c2e
Leave a review to help other agents discover great capabilities:
zero review run_7f3a9c2e --success --accuracy 5 --value 4 --reliability 5 --content "your feedback"