name: agenthero-ai description: AgentHero AI - Hierarchical multi-agent orchestration system with PM coordination, file-based state management, and interactive menu interface. Use when managing complex multi-agent workflows, coordinating parallel sub-agents, or organizing large project tasks with multiple specialists. All created agents use aghero- prefix. version: 2.0.0
AgentHero AI Skill (V2.0)
Comprehensive orchestration utilities for managing hierarchical multi-agent systems with PM coordination, state management, and topic-based organization.
Overview
This skill provides Python-based utilities for:
- State Management: Create, read, update state files for orchestration (V2.0)
- Topic Lifecycle: Initialize, resume, archive project topics
- Task Coordination: Manage sub-agent tasks and dependencies
- Token Tracking: Monitor and report token usage across agents
- SessionStart Hook: Display active topics on Claude Code startup
When Claude Should Use This Skill
Auto-activate when:
- PM orchestrator needs to manage state files
- Creating or updating topic metadata
- Initializing sub-agent task states
- Archiving completed topics
- Reading orchestration state for resume
Directory Structure (V2.0)
.claude/
├── agents/
│ ├── agenthero-ai/ # PM agent
│ │ ├── agent.md
│ │ └── orchestrated-sub-agent-template.md
│ └── state/ # Runtime state
│ └── agenthero-ai/ # V2.0 namespace
│ ├── topics.json # ✅ Single source of truth
│ ├── topics/ # Topic directories
│ │ └── {topic-slug}/
│ │ ├── task-{id}-{name}.json
│ │ └── messages.json
│ └── archive/ # Completed topics
│
└── skills/
└── agenthero-ai/
├── skill.md # This file
├── scripts/ # Python utilities (V2.0)
│ ├── topic_manager.py # Topic lifecycle
│ ├── state_manager.py # State CRUD operations
│ ├── utils.py # Shared utilities
│ ├── setup_project_structure.py # Directory setup
│ ├── finalize_topic.py # Topic completion
│ ├── check_topics_file.py # Validation
│ └── get_topics_quiet.sh # SessionStart hook
└── templates/
└── state-templates.json # State file schemas
Python Utilities (V2.0)
1. Topic Manager (scripts/topic_manager.py)
Purpose: Manage topic lifecycle (V2.0 - uses topics.json)
Commands:
create_topic <title>- Initialize new topic in topics.jsonlist_active_topics- List non-completed topicslist_completed_topics- List completed topicsget_topic_status <slug>- Get topic progress and metricstouch_topic <slug>- Update last active timeupdate_topic_progress <slug>- Recalculate progress from tasksarchive_topic <slug>- Move topic to archive directoryresume_topic <slug>- Update last active and return statusget_active_topics_summary- Get summary for SessionStart hookcomplete_topic <slug>- Mark as completed and archivedelete_topic <slug>- Delete topic (use with caution)
Usage Examples:
# Create new topic (V2.0)
python .claude/skills/agenthero-ai/scripts/topic_manager.py \
create_topic \
"Add JWT authentication" \
--description "Implement JWT-based auth with tokens and middleware"
# List active topics
python .claude/skills/agenthero-ai/scripts/topic_manager.py \
list_active_topics
# Get topic status (reads from topics.json)
python .claude/skills/agenthero-ai/scripts/topic_manager.py \
get_topic_status \
"auth-system-jwt"
# Archive completed topic
python .claude/skills/agenthero-ai/scripts/topic_manager.py \
archive_topic \
"auth-system-jwt"
# Get active topics summary (SessionStart hook)
python .claude/skills/agenthero-ai/scripts/topic_manager.py \
get_active_topics_summary
2. State Manager (scripts/state_manager.py)
Purpose: CRUD operations for state files (V2.0)
Commands:
create_state_file <path> <template>- Initialize state file from templateread_state <path> <field>- Read specific field from stateupdate_state <path> <field> <value>- Update state fieldappend_log <path> <level> <message>- Append log entryset_task_status <path> <status>- Update task statustrack_file_change <path> <file> <change_type>- Track file changeupdate_progress <path> <progress>- Update progress (0-100)validate_state <path>- Validate JSON structureset_blocking_question <path> <question>- Set blocking questionanswer_question <path> <answer>- Answer blocking questionset_task_result <path> <result>- Set task completion result
Usage Examples:
# Create new task state
python .claude/skills/agenthero-ai/scripts/state_manager.py \
create_state_file \
".claude/agents/state/agenthero-ai/topics/auth-system/task-001-backend.json" \
"task-state"
# Append log entry
python .claude/skills/agenthero-ai/scripts/state_manager.py \
append_log \
".claude/agents/state/agenthero-ai/topics/auth-system/task-001-backend.json" \
"info" \
"Starting database schema design"
# Read current status
python .claude/skills/agenthero-ai/scripts/state_manager.py \
read_state \
".claude/agents/state/agenthero-ai/topics/auth-system/task-001-backend.json" \
"status"
# Update progress
python .claude/skills/agenthero-ai/scripts/state_manager.py \
update_progress \
".claude/agents/state/agenthero-ai/topics/auth-system/task-001-backend.json" \
50
3. Utility Functions (scripts/utils.py)
Purpose: Shared helper functions
Functions:
find_project_root()- Find project root by locating .claude directoryslugify(text)- Convert text to URL-safe sluggenerate_task_id(topic_slug)- Generate unique task IDtimestamp_iso()- Get ISO 8601 timestamp with timezoneatomic_write(path, content)- Atomic file write (supports dict/list/str)ensure_directory(path)- Create directory if neededread_json_file(path)- Read and parse JSON fileread_json_field(path, field)- Read specific JSON fieldupdate_json_field(path, field, value)- Update JSON fieldappend_json_array(path, field, value)- Append to JSON arrayvalidate_json(path)- Validate JSON structure
Usage (imported by other scripts):
from utils import (
find_project_root, slugify, timestamp_iso,
atomic_write, read_json_file
)
# Generate slug
slug = slugify("Add JWT Authentication")
# Returns: "add-jwt-authentication"
# Atomic write (prevents corruption)
atomic_write("state.json", {"status": "completed"})
# Find project root
project_root = find_project_root()
# Returns: Path to directory containing .claude/
4. Setup Project Structure (scripts/setup_project_structure.py)
Purpose: Create initial directory structure for topics
Usage:
# Create Project-tasks/{slug}/ structure
python .claude/skills/agenthero-ai/scripts/setup_project_structure.py \
"landing-page-builder"
# Creates:
# - Project-tasks/landing-page-builder/
# - Project-tasks/landing-page-builder/spec/
# - Project-tasks/landing-page-builder/deliverables/
5. Finalize Topic (scripts/finalize_topic.py)
Purpose: Mark topic as completed and archive
Usage:
# Finalize topic (V2.0)
python .claude/skills/agenthero-ai/scripts/finalize_topic.py \
"landing-page-builder"
# Actions:
# 1. Marks status as "completed" in topics.json
# 2. Sets completedAt timestamp
# 3. Archives topic directory
6. Check Topics File (scripts/check_topics_file.py)
Purpose: Validate topics.json structure
Usage:
# Validate topics registry (V2.0)
python .claude/skills/agenthero-ai/scripts/check_topics_file.py --summary
# Returns summary of topics.json health
7. SessionStart Hook (scripts/get_topics_quiet.sh)
Purpose: Display active topics on Claude Code startup
Usage (configured in .claude/settings.local.json):
bash .claude/skills/agenthero-ai/scripts/get_topics_quiet.sh
# Output (if topics exist):
# Found 2 active topic(s):
# • Landing Page Builder (45% complete, 3/5 tasks)
# • API Integration (20% complete, 1/4 tasks)
# Output (if no topics):
# No pending topics - ready for new work!
State File Templates (V2.0)
Templates are stored in templates/state-templates.json:
Task State Template
{
"taskId": "",
"focusArea": "",
"agentName": "",
"status": "pending",
"assignedAt": "",
"startedAt": null,
"completedAt": null,
"progress": 0,
"currentOperation": null,
"logs": [],
"filesCreated": [],
"filesModified": [],
"blockingQuestion": null,
"result": null,
"error": null,
"tokenUsage": {
"total": 0,
"operations": []
}
}
Integration with PM Orchestrator
The PM agent (agenthero-ai) uses these utilities for:
1. Topic Initialization
# PM creates new topic (V2.0)
python .claude/skills/agenthero-ai/scripts/topic_manager.py \
create_topic "User login feature" \
--description "Create login with validation"
# Returns: user-login-feature (slug)
2. Directory Setup
# PM creates Project-tasks structure
python .claude/skills/agenthero-ai/scripts/setup_project_structure.py \
"user-login-feature"
3. Task State Management
# PM initializes sub-agent task
python .claude/skills/agenthero-ai/scripts/state_manager.py \
create_state_file \
".claude/agents/state/agenthero-ai/topics/login-feature/task-001-frontend.json" \
"task-state"
4. Progress Monitoring
# PM reads task status
python .claude/skills/agenthero-ai/scripts/state_manager.py \
read_state \
".claude/agents/state/agenthero-ai/topics/login-feature/task-001-frontend.json" \
"status"
5. Topic Completion
# PM finalizes topic (V2.0)
python .claude/skills/agenthero-ai/scripts/finalize_topic.py \
"login-feature"
Integration with Sub-Agents
Sub-agents use state_manager for logging and updates:
# Sub-agent logs progress
python .claude/skills/agenthero-ai/scripts/state_manager.py \
append_log \
"$STATE_FILE" \
"info" \
"Creating LoginForm component"
# Sub-agent updates progress
python .claude/skills/agenthero-ai/scripts/state_manager.py \
update_progress \
"$STATE_FILE" \
40
# Sub-agent tracks file changes
python .claude/skills/agenthero-ai/scripts/state_manager.py \
track_file_change \
"$STATE_FILE" \
"src/components/LoginForm.tsx" \
"created"
Best Practices
- Always validate JSON before writing (automatic in atomic_write)
- Use atomic writes to prevent corruption (built-in)
- Log regularly (every 30-60 seconds minimum)
- Update progress milestones (25%, 50%, 75%, 100%)
- Track file changes in state files
- Archive completed topics for history (automatic via finalize_topic.py)
Error Handling
All scripts include error handling:
- Validate input parameters
- Check file existence
- Verify JSON structure (automatic validation)
- Return meaningful error codes (0 = success, 1 = error)
- Log errors to stderr (colored output)
Performance
State operations are optimized:
- Atomic writes prevent corruption
- Minimal file I/O
- Path resolution caches project root
- JSON validation only when needed
Security
State files may contain sensitive data:
- Gitignored by default (
.claude/agents/state/) - File permissions: 644 (owner read/write)
- No credentials stored in state
- Audit trail via logs array
Troubleshooting
Invalid JSON error:
# Validate state file
python .claude/skills/agenthero-ai/scripts/state_manager.py \
validate_state \
".claude/agents/state/agenthero-ai/topics/my-topic/task-001.json"
State file not found:
# Check topics registry
cat .claude/agents/state/agenthero-ai/topics.json | python -m json.tool
Wrong directory created:
# Ensure scripts run from project root OR
# Use absolute paths (scripts auto-detect project root via find_project_root())
Version
Version: 2.0.0 Created: 2025-10-22 Updated: 2025-10-24 (Python migration complete)
Migration Notes (V1 → V2)
Key Changes:
- ✅ Bash scripts → Python scripts
- ✅ Individual topic.json files → Single topics.json registry
- ✅ Relative paths → Absolute path resolution
- ✅ Manual JSON handling → Atomic write with validation
- ✅ List support added to atomic_write()
Support
For issues:
- Check JSON validity:
python -m json.tool < file.json - Validate topics.json:
check_topics_file.py --summary - Review state structure: See
STATE-STRUCTURE-V2.md - Verify directory structure exists
- Check file permissions
Part of: Hierarchical Multi-Agent Orchestration System V2.0 Related: agenthero-ai agent, orchestrated-sub-agent-template