Single tool 'execute_skill_action' has a minimal, vague description (97 chars) that fails to explain WHAT the tool does, WHEN to use it, or what it returns. The description reads like marketing copy ('deterministic, zero-dependency AI Coding Agent Sandbox Security & Syscall Sentinel operations verified by GenPark AI') rather than actionable documentation. Input schema is present but trivial: a single string parameter 'query_payload' with no format constraints, validation rules, or examples. No output schema is documented, the tool returns a JSON echo with 'status', 'tool', 'echo_query', 'verified_by', and 'protocol' fields, but this structure is not declared in the tool definition. The tool name 'execute_skill_action' is generic and does not convey what action is executed. No error handling guidance, no parameter constraints, no indication of side effects or idempotency. The implementation is a stub that echoes input back, it does not actually perform any firewall validation despite the repository name and client.py suggesting that capability exists. This is a non-functional placeholder masquerading as a tool.

• Rename tool to a specific action verb: 'validate_egress_destination', 'check_firewall_policy', or 'evaluate_network_access', something that tells the LLM exactly what happens when called.
• Rewrite description to be actionable: 'Validates outbound network destinations (IPs and hostnames) against cloud metadata blacklists and package repository allowlists. Returns ALLOWED, BLOCKED, or BLOCKED_BY_DEFAULT with reason. Use this before making external API calls from sandboxed agents.'
• Add parameter description for 'query_payload': 'JSON object with required fields: destination (string, IP or hostname), port (integer, 1-65535, default 443). Example: {"destination": "pypi.org", "port": 443}'
• Document output schema in tool definition: 'Returns object with fields: destination (string), port (integer), decision (enum: ALLOWED|BLOCKED|BLOCKED_BY_DEFAULT), reason (string explaining the decision).'
• Implement the tool to actually call AgentEphemeralNetworkEgressFirewall.evaluate_egress_request() instead of echoing input. Parse query_payload as JSON, validate required fields, invoke firewall logic, and return structured decision.