Single tool 'execute_skill_action' has a minimal description (97 chars) that lacks actionable context for LLM selection. Input schema is present but parameter 'query_payload' has only a generic description ('Input execution payload for this skill'). No output schema is documented, the tool returns a hardcoded JSON string with no field definitions. No error handling guidance, no parameter constraints, and no indication of what 'deterministic, zero-dependency Long-Horizon Coding & Memory operations' actually means. The tool name uses 'execute' (generic verb) rather than a specific action verb. No evidence of idempotency, permission gates, or security considerations. This is a stub implementation masquerading as a production tool.

• Rename tool to a specific action verb: 'verify_codebase_invariants', 'assert_patch_compliance', or 'check_code_governance'. This clarifies intent without reading the description.
• Document the output schema with typed fields: {status: 'SUCCESS'|'FAILURE', violations: [{type, location, severity}], audit_url: string}. Include field descriptions so LLMs know what to extract.
• Expand parameter description: 'query_payload (string): A code patch or diff to validate against codebase invariants. Format: unified diff or raw code snippet. Max 10KB. Example: "def authenticate(req): ..."'
• Add error handling: 'If invariants are violated, return status=FAILURE with violations array. Include actionable guidance: "Violation: external dependency detected. Remove import or add to whitelist."'
• Document tool purpose in description: 'Validates code patches against GenPark governance rules (zero external dependencies, no breaking API changes). Call before merging code to prevent policy violations. Returns audit trail URL for compliance tracking.'