AdLoop provides three tools with explicit schemas and descriptions. Naming is action-verb-forward (run_, estimate_, draft_) and clear. However, parameter descriptions are sparse and lack validation guidance, output schemas are not formally documented, and error handling is not visible in the code. Tool descriptions are adequate but could be more specific about preconditions and expected outcomes. The use of ToolAnnotations (readOnlyHint/destructiveHint) is present and correct, but overall parameter quality falls short of production baseline (94% of A+ tools have full param descriptions; AdLoop is closer to 40%).

• Add formal output schema definitions for all three tools. Include response examples showing the structure of 'formatted results', 'forecast metrics', and 'conversion action preview'. Document pagination (if applicable) and field meanings.
• Expand parameter descriptions to include validation rules, enums, and ranges. E.g., 'format: One of table|csv|json (default: table)', 'geo_target_id: Google Ads geo constant ID; common: 2276=Germany, 2840=USA. See list_geo_targets() to discover.',
• For draft_create_conversion_action, document parameter dependencies explicitly: 'If type_ is PHONE_CALL_LEAD, phone_call_duration_seconds must be set (0-1800 seconds). Ignored for other types.'
• Add error recovery guidance in tool descriptions. E.g., 'If run_gaql returns an invalid query error, verify GAQL syntax at [docs_link]. If customer_id lookup fails, call get_accessible_customers() first.'
• Convert 'format' and 'type_' parameters to explicit enum types in the JSON schema, not just string descriptions. This enables LLM clients to validate against the schema before calling.
• Add a discovery tool (e.g., 'list_conversion_action_types', 'list_geo_targets') to help agents understand valid enum values without hardcoding them.