70 lines
4.2 KiB
Markdown
70 lines
4.2 KiB
Markdown
---
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name: mma-orchestrator
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description: Enforces the 4-Tier Hierarchical Multi-Model Architecture (MMA) within Gemini CLI using Token Firewalling and sub-agent task delegation.
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---
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# MMA Token Firewall & Tiered Delegation Protocol
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You are operating within the MMA Framework, acting as either the **Tier 1 Orchestrator** (for setup/init) or the **Tier 2 Tech Lead** (for execution). Your context window is extremely valuable and must be protected from token bloat (such as raw, repetitive code edits, trial-and-error histories, or massive stack traces).
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To accomplish this, you MUST delegate token-heavy or stateless tasks to **Tier 3 Workers** or **Tier 4 QA Agents** by spawning secondary Gemini CLI instances via `run_shell_command`.
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**CRITICAL Prerequisite:**
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To ensure proper environment handling and logging, you MUST NOT call the `gemini` command directly for sub-tasks. Instead, use the wrapper script:
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`uv run python scripts/mma_exec.py --role <Role> "..."`
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## 1. The Tier 3 Worker (Execution)
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When performing code modifications or implementing specific requirements:
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1. **DO NOT** perform large code writes yourself.
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2. **DO** construct a single, highly specific prompt with a clear objective.
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3. **DO** spawn a Tier 3 Worker.
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*Command:* `uv run python scripts/mma_exec.py --role tier3-worker "Implement [SPECIFIC_INSTRUCTION] in [FILE_PATH]. Follow TDD and return success status or code changes."`
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4. The Tier 3 Worker is stateless and has tool access for file I/O.
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## 2. The Tier 4 QA Agent (Diagnostics)
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If you run a test or command that fails with a significant error or large traceback:
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1. **DO NOT** analyze the raw logs in your own context window.
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2. **DO** spawn a stateless Tier 4 agent to diagnose the failure.
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3. *Command:* `uv run python scripts/mma_exec.py --role tier4-qa "Analyze this failure and summarize the root cause: [LOG_DATA]"`
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4. **Mandatory Research-First Protocol:** Avoid direct `read_file` calls for any file over 50 lines. Use `get_file_summary`, `py_get_skeleton`, or `py_get_code_outline` first to identify relevant sections. Use `git diff` to understand changes.
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## 3. Persistent Tech Lead Memory (Tier 2)
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Unlike the stateless sub-agents (Tiers 3 & 4), the **Tier 2 Tech Lead** maintains persistent context throughout the implementation of a track. Do NOT apply "Context Amnesia" to your own session during track implementation. You are responsible for the continuity of the technical strategy.
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## 4. AST Skeleton & Outline Views
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To minimize context bloat for Tier 2 & 3:
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1. Use `py_get_code_outline` or `get_tree` to map out the structure of a file or project.
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2. Use `py_get_skeleton` and `py_get_imports` to understand the interface, docstrings, and dependencies of modules.
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3. Use `py_find_usages` to pinpoint where a function or class is called instead of searching the whole codebase.
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4. Use `py_check_syntax` after making string replacements to ensure the file is still syntactically valid.
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5. Only use `read_file` with `start_line` and `end_line` for specific implementation details once target areas are identified.
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6. Tier 3 workers MUST NOT read the full content of unrelated files.
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<examples>
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### Example 1: Spawning a Tier 4 QA Agent
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**User / System:** `pytest tests/test_gui.py` failed with 400 lines of output.
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**Agent (You):**
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```json
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{
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"command": "python scripts/mma_exec.py --role tier4-qa \"Summarize this stack trace into a 20-word fix: [snip first 30 lines...]\"",
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"description": "Spawning Tier 4 QA to compress error trace statelessly."
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}
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```
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### Example 2: Spawning a Tier 3 Worker
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**User:** Please implement the `ASTParser` class in `file_cache.py` as defined in Track 1.
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**Agent (You):**
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```json
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{
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"command": "python scripts/mma_exec.py --role tier3-worker \"Read file_cache.py and implement the ASTParser class using tree-sitter. Ensure you preserve docstrings but strip function bodies. Output the updated code.\"",
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"description": "Delegating implementation to a Tier 3 Worker."
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}
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```
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</examples>
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<triggers>
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- When asked to write large amounts of boilerplate or repetitive code (Coding > 50 lines).
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- When encountering a large error trace from a shell execution (Errors > 100 lines).
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- When explicitly instructed to act as a "Tech Lead" or "Orchestrator".
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- When managing complex, multi-file Track implementations.
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</triggers> |