ARBuilder

Instructions

Implementation Reference

• src/mcp/tools/ask_stylus.py:251-380 (handler)

  The `execute` method of `AskStylusTool` class handles the logic for answering questions about Stylus development, including input validation, context retrieval, prompt generation, LLM interaction, and response parsing.

  def execute(
      self,
      question: str,
      code_context: Optional[str] = None,
      question_type: str = "general",
      target_version: Optional[str] = None,
      **kwargs,
  ) -> dict:
      """
      Answer a question about Stylus development.
  
      Args:
          question: The question to answer.
          code_context: Optional code snippet for context (e.g., for debugging).
          question_type: Type of question (concept, debugging, comparison, howto, general).
          target_version: Target stylus-sdk version for version-specific guidance.
  
      Returns:
          Dict with answer, code_examples, references, follow_up_questions.
      """
      # Validate input
      if not question or not question.strip():
          return {"error": "Question is required and cannot be empty"}
  
      question = question.strip()
  
      # Check if question is Stylus-related
      stylus_keywords = [
          "stylus",
          "rust",
          "contract",
          "arbitrum",
          "storage",
          "entrypoint",
          "sol_storage",
          "erc",
          "token",
          "deploy",
          "wasm",
          "sdk",
      ]
      is_stylus_related = any(kw in question.lower() for kw in stylus_keywords)
  
      if not is_stylus_related and not code_context:
          return {
              "answer": (
                  "This question doesn't appear to be"
                  " related to Stylus or Arbitrum"
                  " development. I'm specialized in"
                  " helping with Stylus smart contract"
                  " development. Please ask about"
                  " Stylus concepts, code,"
                  " or debugging."
              ),
              "code_examples": [],
              "references": [],
              "follow_up_questions": [
                  "What is Stylus and how does it work?",
                  "How do I create my first Stylus contract?",
                  "What are the benefits of Stylus over Solidity?",
              ],
          }
  
      # Default to main version if not specified
      if not target_version:
          target_version = get_main_version()
  
      try:
          # Retrieve relevant context with version-aware scoring
          context_result = self.context_tool.execute(
              query=question,
              n_results=5,
              content_type="all",
              rerank=True,
              category_boosts=None,  # Use default Stylus-focused boosts
              target_version=target_version,
          )
  
          references = []
          context_text = ""
  
          if "contexts" in context_result:
              for ctx in context_result["contexts"]:
                  references.append(
                      {
                          "title": ctx["metadata"].get("title", "Reference"),
                          "source": ctx["source"],
                          "relevance": f"Relevance score: {ctx['relevance_score']:.2f}",
                      }
                  )
                  context_text += (
                      f"\n--- Reference: {ctx['source']} ---\n{ctx['content'][:1200]}\n"
                  )
  
          # Build prompt
          user_prompt = self._build_prompt(
              question=question,
              code_context=code_context,
              question_type=question_type,
              context_text=context_text,
          )
  
          # Generate answer with version-aware system prompt
          messages = [
              {"role": "system", "content": get_system_prompt(target_version)},
              {"role": "user", "content": user_prompt},
          ]
  
          response = self._call_llm(
              messages=messages,
              temperature=0.3,
              max_tokens=2048,
          )
  
          # Parse response
          answer, code_examples = self._parse_response(response, target_version=target_version)
  
          # Generate follow-up questions
          follow_up_questions = self._generate_follow_ups(question, answer)
  
          return {
              "answer": answer,
              "code_examples": code_examples,
              "references": references[:5],  # Limit to 5 references
              "follow_up_questions": follow_up_questions,
          }
  
      except Exception as e:
          return {"error": f"Failed to answer question: {str(e)}"}