Server exposes 5 tools with HTTP transport and x402 payment integration. All tools have descriptions and input schemas visible in main.py. However, critical gaps undermine quality: (1) Parameter descriptions are sparse or missing context, e.g., 'agent_id' lacks guidance on format/resolution; (2) No output schemas documented, LLMs cannot predict response structure; (3) Alias parameters (requested_amount/amount, target_api/api_url) create ambiguity and violate single-responsibility naming; (4) Error handling is absent, no recovery guidance or actionable error messages; (5) Tool names lack clear verb-noun structure (budget_check, budget_record, record_payment are vague about side effects). Baseline: 549 production tools average 194-char descriptions; these average ~80 chars with minimal context. No tool reaches A-grade quality.

• Document output schemas for all 5 tools. Example for budget_check: {allow: boolean, approval_required: boolean, remaining_budget: number, audit_status: string, risk_level: string}. This enables LLMs to chain tools and extract correct fields.
• Remove alias parameters. Consolidate requested_amount + amount → amount; target_api + api_url → api_url. Add a note in the description: 'Accepts both for backward compatibility; prefer amount.'
• Expand parameter descriptions to 100 - 150 chars. For agent_id, add: 'Unique identifier for the AI agent (alphanumeric, max 64 chars). If not provided, defaults to "default-agent". Used to track per-agent spending limits.'
• Add error handling examples in tool descriptions. E.g., budget_check: 'Returns {allow: false, reason: "Daily limit exceeded"} if spending would exceed the daily_limit. Call budget_report to see current usage.'
• Rename tools for clarity: budget_check → verify_budget_approval; budget_record → log_transaction; record_payment → record_x402_payment. This makes intent obvious from the name alone.