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refactor: orchestrator pre-selects features for all agents
Replace agent-initiated feature selection with orchestrator pre-selection for both coding and testing agents. This ensures Mission Control displays correct feature numbers for testing agents (previously showed "Feature #0"). Key changes: MCP Server (mcp_server/feature_mcp.py): - Add feature_get_by_id tool for agents to fetch assigned feature details - Remove obsolete tools: feature_get_next, feature_claim_next, feature_claim_for_testing, feature_get_for_regression - Remove helper functions and unused imports (text, OperationalError, func) Orchestrator (parallel_orchestrator.py): - Change running_testing_agents from list to dict[int, Popen] - Add claim_feature_for_testing() with random selection - Add release_testing_claim() method - Pass --testing-feature-id to spawned testing agents - Use unified [Feature #X] output format for both agent types Agent Entry Points: - autonomous_agent_demo.py: Add --testing-feature-id CLI argument - agent.py: Pass testing_feature_id to get_testing_prompt() Prompt Templates: - coding_prompt.template.md: Update to use feature_get_by_id - testing_prompt.template.md: Update workflow for pre-assigned features - prompts.py: Update pre-claimed headers for both agent types WebSocket (server/websocket.py): - Simplify tracking with unified [Feature #X] pattern - Remove testing-specific parsing code Assistant (server/services/assistant_chat_session.py): - Update help text with current available tools Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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Auto
@@ -47,8 +47,9 @@ API_ENV_VARS = [
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# Read-only feature MCP tools
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READONLY_FEATURE_MCP_TOOLS = [
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"mcp__features__feature_get_stats",
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"mcp__features__feature_get_next",
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"mcp__features__feature_get_for_regression",
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"mcp__features__feature_get_by_id",
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"mcp__features__feature_get_ready",
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"mcp__features__feature_get_blocked",
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]
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# Feature management tools (create/skip but not mark_passing)
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@@ -124,8 +125,9 @@ If the user asks you to modify code, explain that you're a project assistant and
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**Feature Management:**
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- **feature_get_stats**: Get feature completion progress
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- **feature_get_next**: See the next pending feature
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- **feature_get_for_regression**: See passing features for testing
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- **feature_get_by_id**: Get details for a specific feature
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- **feature_get_ready**: See features ready for implementation
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- **feature_get_blocked**: See features blocked by dependencies
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- **feature_create**: Create a single feature in the backlog
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- **feature_create_bulk**: Create multiple features at once
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- **feature_skip**: Move a feature to the end of the queue
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@@ -24,11 +24,17 @@ _count_passing_tests = None
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logger = logging.getLogger(__name__)
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# Pattern to extract feature ID from parallel orchestrator output (coding agents)
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# Pattern to extract feature ID from parallel orchestrator output
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# Both coding and testing agents now use the same [Feature #X] format
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FEATURE_ID_PATTERN = re.compile(r'\[Feature #(\d+)\]\s*(.*)')
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# Pattern to extract testing agent output
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TESTING_AGENT_PATTERN = re.compile(r'\[Testing\]\s*(.*)')
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# Pattern to detect testing agent start message (includes feature ID)
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# Matches: "Started testing agent for feature #123 (PID xxx)"
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TESTING_AGENT_START_PATTERN = re.compile(r'Started testing agent for feature #(\d+)')
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# Pattern to detect testing agent completion
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# Matches: "Feature #123 testing completed" or "Feature #123 testing failed"
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TESTING_AGENT_COMPLETE_PATTERN = re.compile(r'Feature #(\d+) testing (completed|failed)')
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# Patterns for detecting agent activity and thoughts
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THOUGHT_PATTERNS = [
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@@ -50,14 +56,14 @@ THOUGHT_PATTERNS = [
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class AgentTracker:
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"""Tracks active agents and their states for multi-agent mode."""
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"""Tracks active agents and their states for multi-agent mode.
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# Use a special key for the testing agent since it doesn't have a fixed feature ID
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TESTING_AGENT_KEY = -1
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Both coding and testing agents are now tracked by their feature ID.
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The agent_type field distinguishes between them.
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"""
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def __init__(self):
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# feature_id -> {name, state, last_thought, agent_index, agent_type}
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# For testing agents, use TESTING_AGENT_KEY as the key
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self.active_agents: dict[int, dict] = {}
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self._next_agent_index = 0
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self._lock = asyncio.Lock()
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@@ -68,35 +74,43 @@ class AgentTracker:
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Returns None if no update should be emitted.
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"""
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# Check for testing agent output first
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testing_match = TESTING_AGENT_PATTERN.match(line)
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if testing_match:
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content = testing_match.group(1)
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return await self._process_testing_agent_line(content)
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# Check for orchestrator status messages first
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# These don't have [Feature #X] prefix
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# Check for feature-specific output (coding agents)
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# Coding agent start: "Started coding agent for feature #X"
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if line.startswith("Started coding agent for feature #"):
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try:
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feature_id = int(re.search(r'#(\d+)', line).group(1))
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return await self._handle_agent_start(feature_id, line, agent_type="coding")
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except (AttributeError, ValueError):
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pass
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# Testing agent start: "Started testing agent for feature #X (PID xxx)"
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testing_start_match = TESTING_AGENT_START_PATTERN.match(line)
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if testing_start_match:
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feature_id = int(testing_start_match.group(1))
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return await self._handle_agent_start(feature_id, line, agent_type="testing")
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# Testing agent complete: "Feature #X testing completed/failed"
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testing_complete_match = TESTING_AGENT_COMPLETE_PATTERN.match(line)
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if testing_complete_match:
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feature_id = int(testing_complete_match.group(1))
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is_success = testing_complete_match.group(2) == "completed"
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return await self._handle_agent_complete(feature_id, is_success)
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# Coding agent complete: "Feature #X completed/failed" (without "testing" keyword)
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if line.startswith("Feature #") and ("completed" in line or "failed" in line) and "testing" not in line:
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try:
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feature_id = int(re.search(r'#(\d+)', line).group(1))
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is_success = "completed" in line
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return await self._handle_agent_complete(feature_id, is_success)
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except (AttributeError, ValueError):
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pass
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# Check for feature-specific output lines: [Feature #X] content
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# Both coding and testing agents use this format now
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match = FEATURE_ID_PATTERN.match(line)
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if not match:
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# Also check for orchestrator status messages
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if line.startswith("Started coding agent for feature #"):
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try:
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feature_id = int(re.search(r'#(\d+)', line).group(1))
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return await self._handle_agent_start(feature_id, line, agent_type="coding")
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except (AttributeError, ValueError):
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pass
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elif line.startswith("Started testing agent"):
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return await self._handle_testing_agent_start(line)
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elif line.startswith("Feature #") and ("completed" in line or "failed" in line):
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try:
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feature_id = int(re.search(r'#(\d+)', line).group(1))
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is_success = "completed" in line
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return await self._handle_agent_complete(feature_id, is_success)
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except (AttributeError, ValueError):
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pass
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elif line.startswith("Testing agent") and ("completed" in line or "failed" in line):
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# Format: "Testing agent (PID xxx) completed" or "Testing agent (PID xxx) failed"
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is_success = "completed" in line
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return await self._handle_testing_agent_complete(is_success)
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return None
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feature_id = int(match.group(1))
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@@ -149,118 +163,6 @@ class AgentTracker:
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return None
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async def _process_testing_agent_line(self, content: str) -> dict | None:
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"""Process output from a testing agent."""
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async with self._lock:
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# Ensure testing agent is tracked
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if self.TESTING_AGENT_KEY not in self.active_agents:
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agent_index = self._next_agent_index
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self._next_agent_index += 1
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self.active_agents[self.TESTING_AGENT_KEY] = {
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'name': AGENT_MASCOTS[agent_index % len(AGENT_MASCOTS)],
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'agent_index': agent_index,
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'agent_type': 'testing',
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'state': 'testing',
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'feature_name': 'Regression Testing',
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'last_thought': None,
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}
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agent = self.active_agents[self.TESTING_AGENT_KEY]
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# Detect state and thought from content
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state = 'testing'
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thought = None
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for pattern, detected_state in THOUGHT_PATTERNS:
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m = pattern.search(content)
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if m:
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state = detected_state
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thought = m.group(1) if m.lastindex else content[:100]
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break
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# Only emit update if state changed or we have a new thought
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if state != agent['state'] or thought != agent['last_thought']:
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agent['state'] = state
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if thought:
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agent['last_thought'] = thought
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return {
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'type': 'agent_update',
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'agentIndex': agent['agent_index'],
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'agentName': agent['name'],
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'agentType': 'testing',
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'featureId': 0, # Testing agents work on random features
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'featureName': agent['feature_name'],
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'state': state,
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'thought': thought,
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'timestamp': datetime.now().isoformat(),
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}
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return None
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async def _handle_testing_agent_start(self, line: str) -> dict | None:
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"""Handle testing agent start message from orchestrator.
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Reuses existing testing agent entry if present to avoid ghost agents in UI.
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"""
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async with self._lock:
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# Reuse existing testing agent entry if present
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existing = self.active_agents.get(self.TESTING_AGENT_KEY)
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if existing:
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agent_index = existing['agent_index']
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agent_name = existing['name']
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else:
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agent_index = self._next_agent_index
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self._next_agent_index += 1
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agent_name = AGENT_MASCOTS[agent_index % len(AGENT_MASCOTS)]
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self.active_agents[self.TESTING_AGENT_KEY] = {
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'name': agent_name,
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'agent_index': agent_index,
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'agent_type': 'testing',
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'state': 'testing',
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'feature_name': 'Regression Testing',
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'last_thought': 'Starting regression tests...',
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}
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return {
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'type': 'agent_update',
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'agentIndex': agent_index,
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'agentName': agent_name,
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'agentType': 'testing',
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'featureId': 0,
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'featureName': 'Regression Testing',
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'state': 'testing',
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'thought': 'Starting regression tests...',
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'timestamp': datetime.now().isoformat(),
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}
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async def _handle_testing_agent_complete(self, is_success: bool) -> dict | None:
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"""Handle testing agent completion."""
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async with self._lock:
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if self.TESTING_AGENT_KEY not in self.active_agents:
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return None
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agent = self.active_agents[self.TESTING_AGENT_KEY]
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state = 'success' if is_success else 'error'
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result = {
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'type': 'agent_update',
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'agentIndex': agent['agent_index'],
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'agentName': agent['name'],
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'agentType': 'testing',
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'featureId': 0,
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'featureName': agent['feature_name'],
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'state': state,
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'thought': 'Tests passed!' if is_success else 'Found regressions',
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'timestamp': datetime.now().isoformat(),
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}
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# Remove from active agents
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del self.active_agents[self.TESTING_AGENT_KEY]
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return result
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async def get_agent_info(self, feature_id: int) -> tuple[int | None, str | None]:
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"""Get agent index and name for a feature ID.
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