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conductor/archive/gemini_cli_parity_20260225/index.md
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conductor/archive/gemini_cli_parity_20260225/index.md
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# Track gemini_cli_parity_20260225 Context
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- [Specification](./spec.md)
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- [Implementation Plan](./plan.md)
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- [Metadata](./metadata.json)
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{
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"track_id": "gemini_cli_parity_20260225",
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"type": "feature",
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"status": "new",
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"created_at": "2026-02-25T00:00:00Z",
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"updated_at": "2026-02-25T00:00:00Z",
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"description": "Make sure gemini cli behavior and feature set have full parity with regular direct gemini api usage in ai_client.py and elsewhere"
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}
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conductor/archive/gemini_cli_parity_20260225/plan.md
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# Implementation Plan: Gemini CLI Parity
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## Phase 1: Infrastructure & Common Logic
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- [x] Task: Initialize MMA Environment `activate_skill mma-orchestrator`
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- [x] Task: Audit `gemini_cli_adapter.py` and `ai_client.py` for parity gaps (Findings: missing count_tokens, safety settings, and robust system prompt handling in CLI adapter)
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- [x] Task: Implement common logging utilities for CLI bridge observability
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- [x] Task: Conductor - User Manual Verification 'Infrastructure & Common Logic' (Protocol in workflow.md)
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## Phase 2: Token Counting & Safety Settings
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- [x] Task: Write failing tests for token estimation in `GeminiCLIAdapter`
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- [x] Task: Implement token counting parity in `GeminiCLIAdapter`
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- [x] Task: Write failing tests for safety setting application in `GeminiCLIAdapter`
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- [x] Task: Implement safety filter application in `GeminiCLIAdapter`
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- [x] Task: Conductor - User Manual Verification 'Token Counting & Safety Settings' (Protocol in workflow.md)
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## Phase 3: Tool Calling Parity & System Instructions
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- [x] Task: Write failing tests for system instruction usage in `GeminiCLIAdapter`
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- [x] Task: Implement system instruction propagation in `GeminiCLIAdapter`
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- [x] Task: Write failing tests for tool call/response mapping in `cli_tool_bridge.py`
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- [x] Task: Synchronize tool call handling between bridge and `ai_client.py`
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- [x] Task: Conductor - User Manual Verification 'Tool Calling Parity & System Instructions' (Protocol in workflow.md)
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## Phase 4: Final Verification & Performance Diagnostics
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- [x] Task: Implement automated parity regression tests comparing CLI vs Direct API outputs
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- [x] Task: Verify bridge latency and error handling robustness
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- [x] Task: Conductor - User Manual Verification 'Final Verification & Performance Diagnostics' (Protocol in workflow.md)
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## Phase 5: Edge Case Resilience & GUI Integration Tests
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- [x] Task: Implement tests for context bleed prevention (filtering non-assistant messages)
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- [x] Task: Implement tests for parameter name resilience (dir_path/file_path aliases)
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- [x] Task: Implement tests for tool call loop termination and payload persistence
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- [x] Task: Conductor - User Manual Verification 'Edge Case Resilience' (Protocol in workflow.md)
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conductor/archive/gemini_cli_parity_20260225/spec.md
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# Specification: Gemini CLI Parity
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## Overview
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Achieve full functional and behavioral parity between the Gemini CLI integration (`gemini_cli_adapter.py`, `cli_tool_bridge.py`) and the direct Gemini API implementation (`ai_client.py`). This ensures that users leveraging the Gemini CLI as a headless backend provider experience the same level of capability, reliability, and observability as direct API users.
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## Functional Requirements
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- **Token Estimation Parity:** Implement accurate token counting for both input and output in the Gemini CLI adapter to match the precision of the direct API.
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- **Safety Settings Parity:** Enable full configuration and enforcement of Gemini safety filters when using the CLI provider.
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- **Tool Calling Parity:** Synchronize tool definition mapping, call handling, and response processing between the CLI bridge and the direct SDK.
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- **System Instructions Parity:** Ensure system prompts and instructions are consistently passed and handled across both providers.
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- **Bridge Robustness:** Enhance the `cli_tool_bridge.py` and adapter to improve latency, error handling (retries), and detailed subprocess observability.
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## Non-Functional Requirements
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- **Observability:** Detailed logging of CLI subprocess interactions for debugging.
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- **Performance:** Minimize the overhead introduced by the bridge mechanism.
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- **Maintainability:** Ensure that future changes to `ai_client.py` can be easily mirrored in the CLI adapter.
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## Acceptance Criteria
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- [ ] Token counts for identical prompts match within a 5% margin between CLI and Direct API.
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- [ ] Safety settings configured in the GUI are correctly applied to CLI sessions.
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- [ ] Tool calls from the CLI are successfully executed and returned via the bridge without loss of context.
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- [ ] System instructions are correctly utilized by the model when using the CLI.
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- [ ] Automated tests verify that responses and tool execution flows are identical for both providers.
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## Out of Scope
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- Performance optimizations for the `gemini` CLI binary itself.
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- Support for non-Gemini CLI providers in this track.
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