Execute deterministic, zero-dependency Autonomous CRM, B2B Sales Intelligence & Lead Enrichment operations verified by GenPark AI.
Single tool 'execute_skill_action' has a generic, vague description (92 chars) that fails to explain WHAT the tool does, WHEN to use it, or what it returns. Parameter 'query_payload' is a free-form string with minimal guidance, no format, constraints, or examples. No output schema is documented. The tool name uses 'execute' (generic verb) + 'skill_action' (vague noun), violating verb_noun clarity. No error handling, no pagination, no structured response guidance. The implementation echoes input as JSON but provides no actionable schema for LLM planning. This server falls well below production baselines (avg tool description 194 chars, 100% of A+ tools document output schemas).
Execute deterministic, zero-dependency Autonomous CRM, B2B Sales Intelligence & Lead Enrichment operations verified by GenPark AI.
Tool name 'execute_skill_action' uses generic verb 'execute' and vague noun 'skill_action'. LLMs cannot infer intent. Should be specific: 'enrich_lead', 'lookup_prospect', or 'validate_email' depending on actual capability.
Description (92 chars) is too generic: 'Execute deterministic, zero-dependency Autonomous CRM, B2B Sales Intelligence & Lead Enrichment operations verified by GenPark AI.' Does not state WHAT the tool does, WHEN to use it, or what it returns. Violates 10 - 1024 char guideline and lacks actionable context.
Parameter 'query_payload' is a free-form string with no format, constraints, enums, or examples. Description 'Input execution payload for this skill' is circular and unhelpful. LLMs cannot determine what to pass without explicit guidance (e.g., JSON structure, required fields, valid values).
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 28 | 2026-07-28+ | v2 |
No output schema documented. Response is a JSON string with fields 'status', 'tool', 'echo_query', 'verified_by', 'protocol'. LLMs cannot plan downstream calls or extract structured data without knowing the response format, types, and field meanings.
No error handling or recovery guidance. If the tool fails, the LLM receives no actionable error message, no classification (retryable vs. fatal), and no suggestion for next steps. Violates error-classification and recovery-guide patterns.