1.7 KiB
1.7 KiB
Implementation Plan: Gemini CLI Parity
Phase 1: Infrastructure & Common Logic
- Task: Initialize MMA Environment
activate_skill mma-orchestrator - Task: Audit
gemini_cli_adapter.pyandai_client.pyfor parity gaps - Task: Implement common logging utilities for CLI bridge observability
- Task: Conductor - User Manual Verification 'Infrastructure & Common Logic' (Protocol in workflow.md)
Phase 2: Token Counting & Safety Settings
- Task: Write failing tests for token estimation in
GeminiCLIAdapter - Task: Implement token counting parity in
GeminiCLIAdapter - Task: Write failing tests for safety setting application in
GeminiCLIAdapter - Task: Implement safety filter application in
GeminiCLIAdapter - Task: Conductor - User Manual Verification 'Token Counting & Safety Settings' (Protocol in workflow.md)
Phase 3: Tool Calling Parity & System Instructions
- Task: Write failing tests for system instruction usage in
GeminiCLIAdapter - Task: Implement system instruction propagation in
GeminiCLIAdapter - Task: Write failing tests for tool call/response mapping in
cli_tool_bridge.py - Task: Synchronize tool call handling between bridge and
ai_client.py - Task: Conductor - User Manual Verification 'Tool Calling Parity & System Instructions' (Protocol in workflow.md)
Phase 4: Final Verification & Performance Diagnostics
- Task: Implement automated parity regression tests comparing CLI vs Direct API outputs
- Task: Verify bridge latency and error handling robustness
- Task: Conductor - User Manual Verification 'Final Verification & Performance Diagnostics' (Protocol in workflow.md)