remove vendor alignment track
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# Track api_vendor_alignment_20260223 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": "api_vendor_alignment_20260223",
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"type": "chore",
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"status": "new",
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"created_at": "2026-02-23T12:00:00Z",
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"updated_at": "2026-02-23T12:00:00Z",
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"description": "Review project codebase, documentation related to project, and make sure agenti vendor apis are being used as properly stated by offical documentation from google for gemini and anthropic for claude."
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}
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# Implementation Plan: API Usage Audit and Alignment
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## Phase 1: Research and Comprehensive Audit [checkpoint: 5ec4283]
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Identify all points of interaction with AI SDKs and compare them with latest official documentation.
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- [x] Task: List and categorize all AI SDK usage in the project.
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- [x] Search for all imports of `google.genai` and `anthropic`.
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- [x] Document specific functions and methods being called.
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- [x] Task: Research latest official documentation for `google-genai` and `anthropic` Python SDKs.
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- [x] Verify latest patterns for Client initialization.
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- [x] Verify latest patterns for Context/Prompt caching.
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- [x] Verify latest patterns for Tool/Function calling.
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- [x] Task: Conductor - User Manual Verification 'Phase 1: Research and Comprehensive Audit' (Protocol in workflow.md)
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## Phase 2: Gemini (google-genai) Alignment [checkpoint: 842bfc4]
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Align Gemini integration with documented best practices.
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- [x] Task: Refactor Gemini Client and Chat initialization if needed.
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- [x] Write Tests
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- [x] Implement Feature
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- [x] Task: Optimize Gemini Context Caching.
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- [x] Write Tests
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- [x] Implement Feature
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- [x] Task: Align Gemini Tool Declaration and handling.
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- [x] Write Tests
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- [x] Implement Feature
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- [x] Task: Conductor - User Manual Verification 'Phase 2: Gemini (google-genai) Alignment' (Protocol in workflow.md)
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## Phase 3: Anthropic Alignment [checkpoint: f0eb538]
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Align Anthropic integration with documented best practices.
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- [x] Task: Refactor Anthropic Client and Message creation if needed.
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- [x] Write Tests
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- [x] Implement Feature
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- [x] Task: Optimize Anthropic Prompt Caching (`cache_control`).
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- [x] Write Tests
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- [x] Implement Feature
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- [x] Task: Align Anthropic Tool Declaration and handling.
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- [x] Write Tests
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- [x] Implement Feature
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- [x] Task: Conductor - User Manual Verification 'Phase 3: Anthropic Alignment' (Protocol in workflow.md)
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## Phase 4: History and Token Management [checkpoint: 0f9f235]
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Ensure accurate token estimation and robust history handling.
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- [x] Task: Review and align token estimation logic for both providers.
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- [x] Write Tests
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- [x] Implement Feature
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- [x] Task: Audit message history truncation and context window management.
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- [x] Write Tests
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- [x] Implement Feature
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- [x] Task: Conductor - User Manual Verification 'Phase 4: History and Token Management' (Protocol in workflow.md)
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## Phase 5: Final Validation and Cleanup [checkpoint: e9126b4]
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- [x] Task: Perform a full test run using `run_tests.py` to ensure 100% pass rate.
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- [x] Task: Conductor - User Manual Verification 'Phase 5: Final Validation and Cleanup' (Protocol in workflow.md)
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# Specification: API Usage Audit and Alignment
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## Overview
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This track involves a comprehensive audit of the "Manual Slop" codebase to ensure that the integration with Google Gemini (`google-genai`) and Anthropic Claude (`anthropic`) SDKs aligns perfectly with their latest official documentation and best practices. The goal is to identify discrepancies, performance bottlenecks, or deprecated patterns and implement the necessary fixes.
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## Scope
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- **Target:** Full codebase audit, with primary focus on `ai_client.py`, `mcp_client.py`, and any other modules interacting with AI SDKs.
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- **Key Areas:**
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- **Caching Mechanisms:** Verify Gemini context caching and Anthropic prompt caching implementation.
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- **Tool Calling:** Audit function declarations, parameter schemas, and result handling.
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- **History & Tokens:** Review message history management, token estimation accuracy, and context window handling.
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## Functional Requirements
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1. **SDK Audit:** Compare existing code patterns against the latest official Python SDK documentation for Gemini and Anthropic.
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2. **Feature Validation:**
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- Ensure `google-genai` usage follows the latest `Client` and `types` patterns.
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- Ensure `anthropic` usage utilizes `cache_control` correctly for optimal performance.
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3. **Discrepancy Remediation:** Implement code changes to align the implementation with documented standards.
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4. **Validation:** Execute tests to ensure that API interactions remain functional and improved.
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## Acceptance Criteria
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- Full audit completed for all AI SDK interactions.
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- Identified discrepancies are documented and fixed.
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- Caching, tool calling, and history management logic are verified against latest SDK standards.
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- All existing and new tests pass successfully.
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## Out of Scope
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- Adding support for new AI providers not already in the project.
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- Major UI refactoring unless directly required by API changes.
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