Three tools with basic verb-noun naming (get_, compare_, analyze_). All have descriptions (194 - 250 chars, within baseline range). Input schemas present with type declarations. However, critical gaps: no output schemas documented, descriptions lack WHEN/WHY guidance, no error recovery hints, no parameter constraints (enums, ranges), and responses are unstructured text rather than structured JSON. Tools return formatted strings instead of typed objects, forcing LLMs to parse free-form output. No pagination support despite potential for large result sets. Security: no secrets exposed, but no permission gates or audit logging.

• Define output schemas as typed JSON objects. E.g., get_token_price should return {symbol: string, price_usd: number, change_24h: number, market_cap: number, volume_24h: number} instead of a formatted string.
• Add enum or pattern constraints to 'symbol' parameter. Document valid CoinGecko coin IDs or link to CoinGecko's ID list. Validate input and return 'Invalid symbol: {symbol}. Valid examples: bitcoin, ethereum, solana' on error.
• Implement pagination for compare_tokens. Add 'limit' (1 - 250, default 50) and 'offset' parameters. Return {coins: [...], total: number, has_more: boolean} to prevent context window overflow.
• Replace Chinese error messages with English and add recovery hints. E.g., 'Symbol not found: xyz. Did you mean: xyztoken? Call get_token_price with a valid CoinGecko ID.'
• Remove example values from descriptions. Replace 'e.g. bitcoin, ethereum' with a formal constraint or link to documentation. Let the schema and parameter type guide the LLM.