An r/LangChain post described nested chains where small prompt changes break downstream logic. This walks the LangSmith + tool-consolidation approach.
Prerequisites
- LangChain stack
- LangSmith account (free tier OK)
- Scavio API key for tool consolidation
Walkthrough
Step 1: Wire LangSmith tracing into the existing chain
Per-call trace.
Python
import os
os.environ['LANGCHAIN_TRACING_V2']='true'
os.environ['LANGCHAIN_API_KEY']='lsv_...'
# Existing chain code; LangSmith picks up automaticallyStep 2: Reproduce the failing case and inspect the trace
What tool fired? What input?
Text
// In LangSmith UI: open the failing run → step through tool calls → confirm which tool firedStep 3: Identify tool-overlap as the root cause (most common)
5 search/scrape tools = LLM coin flip.
Text
// If 3-5 tools have overlapping descriptions, the LLM picks differently per prompt phrasing.Step 4: Consolidate to one Scavio MCP for search/scrape
Replace 3-5 tools with one.
Bash
claude mcp add scavio https://mcp.scavio.dev/mcp --header 'x-api-key: $SCAVIO_API_KEY'
// Or in LangChain: a single ScavioSearchTool wrapperStep 5: Add explicit routing rules in chain config or system prompt
Don't let the LLM coin-flip.
Text
// 'For product questions, call retriever_a. For policy questions, call retriever_b. For web search, call scavio.search. NEVER call multiple of these.'Step 6: Re-run the failing case and confirm trace shows correct routing
Loop closed.
Text
// LangSmith trace should show: prompt → routing decision → correct tool → answer.Python Example
Python
# A 4-hour debug rabbit-hole pays back the LangSmith subscription many times. Tool consolidation pays back token cost in ~2 weeks.JavaScript Example
JavaScript
// Same in TS via langchain-js + LangSmith.Expected Output
JSON
LangChain stack with traceable per-call inspection + consolidated tool surface (Scavio replacing multiple search tools) + explicit routing rules. Bugs diagnosable in minutes.