MCP server for aggregating influencer affiliate attribution conversions and computing commission metrics
This MCP server has severe definition quality issues. Tool definitions are minimal with insufficient descriptions, missing parameter documentation, and no visible input schemas in the code. The server appears to be a stub implementation with mock responses rather than a production-grade integration. Tool naming is generic ('execute_skill_action'), parameter descriptions are sparse, and there is no evidence of schema validation or proper error handling.
Aggregate affiliate conversions for a creator's promo code over a specified tracking window and compute commission metrics
Execute the influencer affiliate attribution conversion aggregator skill
Tool 'execute_skill_action' has no visible input schema in source code. Schema scoring rule requires 0 for missing schemas.
Tool 'execute_skill_action' has generic name that does not follow verb_noun convention. Name does not convey specific action, 'execute_skill_action' is too vague. Should be 'aggregate_conversions', 'get_affiliate_metrics', or similar.
Parameter 'creator_affiliate_code' description states only the format and example ('SARAH20') but provides no context on what the code is used for or validation rules. Description is functional but minimal (72 chars including default). No enum constraint despite expected fixed format.
Parameter 'tracking_window_days' lacks minimum/maximum bounds. Unbounded integer invites absurd values (negative days, 999999 days). Should specify valid range (e.g., 1-365).
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 24 | 2026-07-28+ | v2 |
No output schema documented for 'aggregate_affiliate_conversions'. Response structure is inferred from example_usage.py (7 fields: attribution_batch_id, promo_code, total_attributed_orders_count, gross_merchandise_value_usd, creator_commission_earned_usd, return_on_ad_spend_roas, commission_payout_export_csv_url) but not formally declared. LLMs cannot plan downstream tool calls without knowing expected response fields.
No error handling defined. No guidance for retryable vs. fatal errors. No recovery suggestions. If the affiliate code does not exist or tracking window is invalid, the tool provides no recovery path.
No input validation visible. Parameters accept defaults but no constraints prevent invalid inputs (negative days, blank affiliate codes, etc.). Early validation with actionable errors is missing.
Tool 'execute_skill_action' appears to be a wrapper/dispatcher but has no documented parameters, input schema, or output schema. It is unclear what 'skill' it executes or what parameters it accepts.