Initial commit
This commit is contained in:
Zhongwei Li
245
hooks/orchestrator_interceptor.py
Executable file
245
hooks/orchestrator_interceptor.py
Executable file
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#!/usr/bin/env python3
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"""
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Orchestrator Interceptor Hook for Claude Code
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Analyzes user prompts and injects orchestrator invocation context for complex tasks.
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"""
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import json
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import sys
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from pathlib import Path
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from loguru import logger
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# Configure loguru
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log_dir = Path.home() / ".claude" / "hook_logs"
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log_dir.mkdir(parents=True, exist_ok=True)
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log_file = log_dir / "orchestrator_hook.log"
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logger.remove()
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logger.add(
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log_file,
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rotation="10 MB",
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retention="30 days",
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format="{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {message}",
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level="INFO"
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)
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logger.add(sys.stderr, level="ERROR")
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def estimate_complexity_tokens(prompt: str, complexity: str) -> dict[str, int]:
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"""Estimate token usage based on complexity assessment."""
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token_estimates = {
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"simple_query": {
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"orchestrator_analysis": 500,
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"agent_execution": 0,
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"total_estimated": 500,
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"cost_usd": 0.0015
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},
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"moderate_task": {
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"orchestrator_analysis": 1000,
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"agent_execution": 5000,
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"total_estimated": 6000,
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"cost_usd": 0.018
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},
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"complex_task": {
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"orchestrator_analysis": 2000,
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"agent_execution": 15000,
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"total_estimated": 17000,
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"cost_usd": 0.051
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},
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"high_complexity": {
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"orchestrator_analysis": 3000,
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"agent_execution": 40000,
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"total_estimated": 43000,
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"cost_usd": 0.129
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}
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}
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return token_estimates.get(complexity, token_estimates["moderate_task"])
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def should_orchestrate(prompt: str) -> tuple[bool, str, str]:
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"""
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Determine if prompt needs orchestration.
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Returns: (needs_orchestration, reason, complexity_level)
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"""
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prompt_lower = prompt.lower()
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word_count = len(prompt.split())
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# 1. Simple queries (skip orchestration)
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simple_patterns = ["what is", "explain", "how do", "why does", "show me", "what does", "define"]
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if any(pattern in prompt_lower for pattern in simple_patterns) and word_count < 20:
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logger.info(f"Classified as SIMPLE QUERY: {prompt[:100]}")
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return False, "simple_query", "simple_query"
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# 2. Explicit orchestration requests
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if "orchestrate" in prompt_lower or "@orchestrate" in prompt_lower:
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logger.info(f"Classified as EXPLICIT ORCHESTRATION REQUEST: {prompt[:100]}")
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return True, "explicit_request", "high_complexity"
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# 3. Cross-layer work (likely needs orchestration)
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layers_mentioned = sum(1 for layer in ["bronze", "silver", "gold"] if layer in prompt_lower)
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if layers_mentioned >= 2:
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logger.info(f"Classified as CROSS-LAYER WORK ({layers_mentioned} layers): {prompt[:100]}")
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return True, "cross_layer_work", "high_complexity"
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# 4. Broad scope indicators
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broad_keywords = ["all", "across", "entire", "multiple", "every"]
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if any(keyword in prompt_lower for keyword in broad_keywords):
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logger.info(f"Classified as BROAD SCOPE: {prompt[:100]}")
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return True, "broad_scope", "complex_task"
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# 5. Code quality sweeps
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quality_keywords = ["linting", "formatting", "type hints", "quality", "refactor", "optimize"]
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scope_keywords = ["all", "entire", "project", "codebase"]
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if any(q in prompt_lower for q in quality_keywords) and any(s in prompt_lower for s in scope_keywords):
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logger.info(f"Classified as QUALITY SWEEP: {prompt[:100]}")
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return True, "quality_sweep", "high_complexity"
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# 6. Multiple file/component work
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if any(keyword in prompt_lower for keyword in ["files", "tables", "classes", "modules", "components"]):
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if any(number in prompt for number in ["all", "multiple", "several", "many"]):
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logger.info(f"Classified as MULTI-COMPONENT WORK: {prompt[:100]}")
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return True, "multi_component", "complex_task"
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# 7. Implementation/feature requests (moderate complexity)
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action_keywords = ["implement", "create", "build", "add", "fix", "update", "modify"]
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if any(action in prompt_lower for action in action_keywords) and word_count > 10:
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logger.info(f"Classified as MODERATE TASK: {prompt[:100]}")
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return True, "implementation_task", "moderate_task"
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# 8. Default to simple handling for very short prompts
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if word_count < 5:
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logger.info(f"Classified as SIMPLE (too short): {prompt[:100]}")
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return False, "too_short", "simple_query"
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# Default: moderate orchestration for safety
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logger.info(f"Classified as DEFAULT MODERATE: {prompt[:100]}")
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return True, "default_moderate", "moderate_task"
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def generate_orchestrator_context(prompt: str, reason: str, complexity: str) -> str:
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"""Generate the context to inject for orchestrator analysis."""
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cost_estimate = estimate_complexity_tokens(prompt, complexity)
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context = f"""
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<orchestrator-analysis-required>
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ORCHESTRATOR INTERCEPTION ACTIVE
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BEFORE responding to the user, you MUST:
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1. Launch the master-orchestrator agent using the Task tool with subagent_type="master-orchestrator"
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2. Pass this user prompt to the orchestrator for complexity analysis:
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USER PROMPT: "{prompt}"
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3. Classification hint: {reason.replace('_', ' ').title()}
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Estimated complexity: {complexity.replace('_', ' ').title()}
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4. COST ESTIMATION (based on initial classification):
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- Orchestrator analysis: ~{cost_estimate['orchestrator_analysis']:,} tokens
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- Estimated agent execution: ~{cost_estimate['agent_execution']:,} tokens
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- Total estimated: ~{cost_estimate['total_estimated']:,} tokens
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- Approximate cost: ${cost_estimate['cost_usd']:.3f} USD
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Note: Actual costs may vary based on orchestrator's final strategy.
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5. The orchestrator will:
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- Assess complexity (Simple/Moderate/High)
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- Determine optimal execution strategy (direct tools vs single agent vs multi-agent)
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- Recommend agent count and decomposition (if multi-agent)
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- Provide detailed execution plan with time estimates
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- Refine cost estimates based on strategy
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6. Present the orchestrator's plan to the user with these options:
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┌─────────────────────────────────────────┐
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│ [1] Execute Plan │
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│ → Proceed with orchestrator's │
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│ recommended approach │
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│ │
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│ [2] Modify Plan │
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│ → User provides feedback to adjust │
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│ strategy (agent count, approach) │
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│ │
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│ [3] Skip Orchestration │
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│ → Handle directly without │
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│ multi-agent coordination │
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└─────────────────────────────────────────┘
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7. Only after user approval, execute according to the chosen approach.
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CRITICAL RULES:
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- Do NOT start any work until orchestrator has analyzed
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- Do NOT proceed without user approval of the plan
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- Present cost estimates clearly in the plan
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- If user chooses [3], handle task directly without orchestrator
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- Log decision and execution to hook logs
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</orchestrator-analysis-required>
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"""
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return context
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def generate_simple_context(prompt: str) -> str:
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"""Generate context for simple queries that don't need orchestration."""
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return f"""
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<simple-query-detected>
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This prompt has been classified as a simple informational query.
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Handle directly without orchestration overhead.
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Query: "{prompt}"
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</simple-query-detected>
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"""
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def main():
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try:
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# Read hook input
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hook_input = json.loads(sys.stdin.read())
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user_prompt = hook_input.get("prompt", "")
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session_id = hook_input.get("session_id", "unknown")
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cwd = hook_input.get("cwd", "unknown")
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logger.info("=" * 80)
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logger.info(f"Hook triggered - Session: {session_id}")
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logger.info(f"CWD: {cwd}")
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logger.info(f"Prompt: {user_prompt}")
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# Analyze prompt
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needs_orchestration, reason, complexity = should_orchestrate(user_prompt)
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# Log decision
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logger.info(f"Decision: {'ORCHESTRATE' if needs_orchestration else 'SKIP'}")
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logger.info(f"Reason: {reason}")
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logger.info(f"Complexity: {complexity}")
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# Generate appropriate context
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if needs_orchestration:
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additional_context = generate_orchestrator_context(user_prompt, reason, complexity)
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cost_estimate = estimate_complexity_tokens(user_prompt, complexity)
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logger.info(f"Cost estimate: ${cost_estimate['cost_usd']:.3f} USD (~{cost_estimate['total_estimated']:,} tokens)")
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else:
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additional_context = generate_simple_context(user_prompt)
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logger.info("No orchestration needed - simple query")
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# Return JSON response
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response = {
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"hookSpecificOutput": {
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"hookEventName": "UserPromptSubmit",
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"additionalContext": additional_context
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}
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}
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logger.info("Hook completed successfully")
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logger.info("=" * 80)
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print(json.dumps(response))
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sys.exit(0)
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except Exception as e:
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logger.error(f"Hook error: {e}")
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logger.exception("Full traceback:")
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# On error, don't block - allow prompt through without modification
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response = {"hookSpecificOutput": {"hookEventName": "UserPromptSubmit", "additionalContext": ""}}
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print(json.dumps(response))
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sys.exit(0)
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if __name__ == "__main__":
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main()
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