Single tool with basic but incomplete definition. Tool name uses Search prefix (acceptable) but lacks the specificity patterns recommend. Description is adequate at 139 characters but lacks critical context about when to use this tool vs alternatives, expected response format, and any prerequisites. Input schema is present with proper JSON Schema structure, but the query parameter description is vague (10 chars: 'A query to search the content with.'). No output schema is documented, the perform_search() function returns free-form text concatenation without describing the structure callers should expect. No error handling guidance for LLMs. No parameter constraints (e.g., max query length, minimum word count). The tool performs a read-only operation (good security posture), but lacks idempotence hints and no mechanism for pagination despite returning top-5 results.

• Expand query parameter description to: 'A search query to find java-tron documentation. Use 2-5 relevant keywords (e.g., "node setup", "API reference", "wallet configuration"). All words must appear in the documentation title or body. Returns up to 5 matching sections with URL and excerpt.'
• Add output schema documentation to the tool definition showing returned object structure: [{ title: string, url: string, excerpt: string }] or similar. Document that truncation to 5 results occurs.
• Enhance tool description to: 'Search the java-tron developer documentation for node setup guides, API references, and configuration instructions. Call this first when users ask about TRON protocol, network setup, or API endpoints. Returns documentation titles with direct links and relevant excerpts.'
• Add error handling with actionable guidance: 'No relevant documentation found. Try: (1) Use fewer, broader keywords (2) Search for specific API methods or node types (3) If index missing, ensure mkdocs build has completed.'
• Document query constraints in the schema via a 'pattern' field or explicit description: 'Queries are split on spaces; all words must match (AND logic). 2-50 character limit. Special characters are stripped.'
• Consider adding optional parameters: offset (for pagination beyond top-5), section_filter (to limit to API vs Setup docs), and result_count (to control output size). This enables composition with preference/context from earlier turns.
• Return structured JSON results instead of free-form text concatenation. LLMs parse structured responses more reliably and token efficiency improves. Example: { results: [ { title, url, excerpt, relevance_score } ], total_matches: N, truncated: boolean }