AI search chat application with Node.js backend supporting deep research and intelligent search workflows using LangGraph and multiple LLM providers
SearChat exhibits significant definition quality gaps. Tool descriptions are present but generic (avg ~60 chars, below 194-char baseline). Input schemas are partially visible but lack critical details: parameter types are declared but descriptions are minimal or missing for many params. The 'search' tool has reasonable schema structure, but tools like 'intentAnalysis', 'rewriteQuery', 'generateQuery', 'reflection', and 'finalizeAnswer' have minimal descriptions (10-30 chars) that fail to explain WHEN to use them or WHAT they return. No output schemas are documented. Error handling is absent, no recovery guidance, no categorization of retryable vs fatal errors. Tool composition shows some promise (search + research + reflection form a coherent pipeline), but the interface lacks the clarity needed for reliable LLM selection and chaining.
Execute chat completion with optional web search context
Generate final answer based on research findings
Generate initial search queries for deep research
Analyze user intent to determine if web search is needed
Reflect on research findings and determine if more research is needed
Conduct web research and gather information from multiple sources
Rewrite user query for better search results
Minimal descriptions for 6 of 8 tools (intentAnalysis, rewriteQuery, generateQuery, reflection, finalizeAnswer). Descriptions under 40 chars fail to explain WHEN to use the tool or WHAT it returns. LLMs cannot reliably select these tools.
No output schemas documented for any tool. LLMs cannot plan downstream calls or extract required fields (e.g., does 'research' return sources? URLs? confidence scores?). Breaks tool chaining.
Parameter descriptions are sparse or missing. 'findings' in reflection, 'queries' in research, 'research' in finalizeAnswer lack detail on expected format, structure, or constraints. LLMs must guess.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 51 | <=2025-11-25 | v2 |
Execute web search queries using configured search engine (SearXNG, Google, Tavily, Sogou, Bing, Zhipu, Bocha, or Exa)
No error handling or recovery guidance. Tools provide no indication of what to do on failure (retry? ask user? fatal?). Agents cannot self-correct.
Tool definitions inferred from file paths and package.json; explicit registration code not visible in provided source. Cannot verify actual schema compliance or runtime behavior.