Single tool 'execute_skill_action' has a basic description (89 chars) and minimal input schema. The schema defines two string parameters (subject, body) with brief descriptions, but lacks critical details: no output schema documentation, no error handling guidance, no parameter constraints (length limits, format requirements), and no explanation of what 'sanitize' means or when to use this tool. The description does not explain prerequisites, expected output structure, or recovery paths. Tool naming is generic ('execute_skill_action') rather than action-specific ('sanitize_email_copy'). The implementation in mcp_server.py is a stub that only prints a JSON status message, no actual tool invocation logic is visible. The client.py contains hardcoded mock responses, not real sanitization logic. This is a proof-of-concept, not production-ready.

• Rename tool to 'sanitize_email_copy' or 'analyze_email_deliverability' to clearly signal the action and match the verb_noun convention.
• Document the complete output schema in the tool description or as a separate schema field. Include all response fields: deliverability_score_pct (number, 0-100), inbox_placement_tier (enum: PRIMARY_INBOX_GUARANTEED, PROMOTIONS_TAB, SPAM_FOLDER), flagged_spam_triggers (array of {word, category, replacement}), sanitized_subject (string), dkim_spf_headers_valid (boolean).
• Add parameter constraints: subject max 200 chars, body max 5000 chars. Explain in descriptions that subject is the email subject line and body is the email message text.
• Add error handling guidance: 'If the email is too long, truncate and retry. If no spam triggers are found, the email is safe to send.' Include examples of recoverable vs. fatal errors.
• Implement the actual tool invocation in mcp_server.py. Currently it only prints a status message. Wire the execute_skill_action tool to call the ColdOutreachDeliverabilitySpamSanitizerClient.sanitize_copy() method and return the real response.