---
name: hive
description: Complete workflow for building, implementing, and testing goal-driven agents. Orchestrates hive-* skills. Use when starting a new agent project, unsure which skill to use, or need end-to-end guidance.
license: Apache-2.0
metadata:
  author: hive
  version: "2.0"
  type: workflow-orchestrator
  orchestrates:
    - hive-concepts
    - hive-create
    - hive-patterns
    - hive-test
    - hive-credentials
    - hive-debugger
---

# Agent Development Workflow

**THIS IS AN EXECUTABLE WORKFLOW. DO NOT explore the codebase or read source files. ROUTE to the correct skill IMMEDIATELY.**

When this skill is loaded, **ALWAYS use the AskUserQuestion tool** to present options:

```
Use AskUserQuestion with these options:
- "Build a new agent" → Then invoke /hive-create
- "Test an existing agent" → Then invoke /hive-test
- "Learn agent concepts" → Then invoke /hive-concepts
- "Optimize agent design" → Then invoke /hive-patterns
- "Set up credentials" → Then invoke /hive-credentials
- "Debug a failing agent" → Then invoke /hive-debugger
- "Other" (please describe what you want to achieve)
```

**DO NOT:** Read source files, explore the codebase, search for code, or do any investigation before routing. The sub-skills handle all of that.

---

Complete Standard Operating Procedure (SOP) for building production-ready goal-driven agents.

## Overview

This workflow orchestrates specialized skills to take you from initial concept to production-ready agent:

1. **Understand Concepts** → `/hive-concepts` (optional)
2. **Build Structure** → `/hive-create`
3. **Optimize Design** → `/hive-patterns` (optional)
4. **Setup Credentials** → `/hive-credentials` (if agent uses tools requiring API keys)
5. **Test & Validate** → `/hive-test`
6. **Debug Issues** → `/hive-debugger` (if agent fails at runtime)

## When to Use This Workflow

Use this meta-skill when:
- Starting a new agent from scratch
- Unclear which skill to use first
- Need end-to-end guidance for agent development
- Want consistent, repeatable agent builds

**Skip this workflow** if:
- You only need to test an existing agent → use `/hive-test` directly
- You know exactly which phase you're in → use specific skill directly

## Quick Decision Tree

```
"Need to understand agent concepts" → hive-concepts
"Build a new agent" → hive-create
"Optimize my agent design" → hive-patterns
"Need client-facing nodes or feedback loops" → hive-patterns
"Set up API keys for my agent" → hive-credentials
"Test my agent" → hive-test
"My agent is failing/stuck/has errors" → hive-debugger
"Not sure what I need" → Read phases below, then decide
"Agent has structure but needs implementation" → See agent directory STATUS.md
```

## Phase 0: Understand Concepts (Optional)

**Skill**: `/hive-concepts`
**Input**: Questions about agent architecture

### When to Use

- First time building an agent
- Need to understand node types, edges, goals
- Want to validate tool availability
- Learning about event loop architecture and client-facing nodes

### What This Phase Provides

- Architecture overview (Python packages, not JSON)
- Core concepts (Goal, Node, Edge, Event Loop, Judges)
- Tool discovery and validation procedures
- Workflow overview

**Skip this phase** if you already understand agent fundamentals.

## Phase 1: Build Agent Structure

**Skill**: `/hive-create`
**Input**: User requirements ("Build an agent that...") or a template to start from

### What This Phase Does

Creates the complete agent architecture:
- Package structure (`exports/agent_name/`)
- Goal with success criteria and constraints
- Workflow graph (nodes and edges)
- Node specifications
- CLI interface
- Documentation

### Process

1. **Create package** - Directory structure with skeleton files
2. **Define goal** - Success criteria and constraints written to agent.py
3. **Design nodes** - Each node approved and written incrementally
4. **Connect edges** - Workflow graph with conditional routing
5. **Finalize** - Agent class, exports, and documentation

### Outputs

- ✅ `exports/agent_name/` package created
- ✅ Goal defined in agent.py
- ✅ 3-5 success criteria defined
- ✅ 1-5 constraints defined
- ✅ 5-10 nodes specified in nodes/__init__.py
- ✅ 8-15 edges connecting workflow
- ✅ Validated structure (passes `uv run python -m agent_name validate`)
- ✅ README.md with usage instructions
- ✅ CLI commands (info, validate, run, shell)

### Success Criteria

You're ready for Phase 2 when:
- Agent structure validates without errors
- All nodes and edges are defined
- CLI commands work (info, validate)
- You see: "Agent complete: exports/agent_name/"

### Common Outputs

The hive-create skill produces:
```
exports/agent_name/
├── __init__.py          (package exports)
├── __main__.py          (CLI interface)
├── agent.py             (goal, graph, agent class)
├── nodes/__init__.py    (node specifications)
├── config.py            (configuration)
├── implementations.py   (may be created for Python functions)
└── README.md            (documentation)
```

### Next Steps

**If structure complete and validated:**
→ Check `exports/agent_name/STATUS.md` or `IMPLEMENTATION_GUIDE.md`
→ These files explain implementation options
→ You may need to add Python functions or MCP tools (not covered by current skills)

**If want to optimize design:**
→ Proceed to Phase 1.5 (hive-patterns)

**If ready to test:**
→ Proceed to Phase 2

## Phase 1.5: Optimize Design (Optional)

**Skill**: `/hive-patterns`
**Input**: Completed agent structure

### When to Use

- Want to add client-facing blocking or feedback edges
- Need judge patterns for output validation
- Want fan-out/fan-in (parallel execution)
- Need error handling patterns
- Want best practices guidance

### What This Phase Provides

- Client-facing interaction patterns
- Feedback edge routing with nullable output keys
- Judge patterns (implicit, SchemaJudge)
- Fan-out/fan-in parallel execution
- Context management and spillover patterns
- Anti-patterns to avoid

**Skip this phase** if your agent design is straightforward.

## Phase 2: Test & Validate

**Skill**: `/hive-test`
**Input**: Working agent from Phase 1

### What This Phase Does

Guides the creation and execution of a comprehensive test suite:
- Constraint tests
- Success criteria tests
- Edge case tests
- Integration tests

### Process

1. **Analyze agent** - Read goal, constraints, success criteria
2. **Generate tests** - The calling agent writes pytest files in `exports/agent_name/tests/` using hive-test guidelines and templates
3. **User approval** - Review and approve each test
4. **Run evaluation** - Execute tests and collect results
5. **Debug failures** - Identify and fix issues
6. **Iterate** - Repeat until all tests pass

### Outputs

- ✅ Test files in `exports/agent_name/tests/`
- ✅ Test report with pass/fail metrics
- ✅ Coverage of all success criteria
- ✅ Coverage of all constraints
- ✅ Edge case handling verified

### Success Criteria

You're done when:
- All tests pass
- All success criteria validated
- All constraints verified
- Agent handles edge cases
- Test coverage is comprehensive

### Next Steps

**Agent ready for:**
- Production deployment
- Integration into larger systems
- Documentation and handoff
- Continuous monitoring

## Phase Transitions

### From Phase 1 to Phase 2

**Trigger signals:**
- "Agent complete: exports/..."
- Structure validation passes
- README indicates implementation complete

**Before proceeding:**
- Verify agent can be imported: `from exports.agent_name import default_agent`
- Check if implementation is needed (see STATUS.md or IMPLEMENTATION_GUIDE.md)
- Confirm agent executes without import errors

### Skipping Phases

**When to skip Phase 1:**
- Agent structure already exists
- Only need to add tests
- Modifying existing agent

**When to skip Phase 2:**
- Prototyping or exploring
- Agent not production-bound
- Manual testing sufficient

## Common Patterns

### Pattern 1: Complete New Build (Simple)

```
User: "Build an agent that monitors files"
→ Use /hive-create
→ Agent structure created
→ Use /hive-test
→ Tests created and passing
→ Done: Production-ready agent
```

### Pattern 1b: Complete New Build (With Learning)

```
User: "Build an agent (first time)"
→ Use /hive-concepts (understand concepts)
→ Use /hive-create (build structure)
→ Use /hive-patterns (optimize design)
→ Use /hive-test (validate)
→ Done: Production-ready agent
```

### Pattern 1c: Build from Template

```
User: "Build an agent based on the deep research template"
→ Use /hive-create
→ Select "From a template" path
→ Pick template, name new agent
→ Review/modify goal, nodes, graph
→ Agent exported with customizations
→ Use /hive-test
→ Done: Customized agent
```

### Pattern 2: Test Existing Agent

```
User: "Test my agent at exports/my_agent"
→ Skip Phase 1
→ Use /hive-test directly
→ Tests created
→ Done: Validated agent
```

### Pattern 3: Iterative Development

```
User: "Build an agent"
→ Use /hive-create (Phase 1)
→ Implementation needed (see STATUS.md)
→ [User implements functions]
→ Use /hive-test (Phase 2)
→ Tests reveal bugs
→ [Fix bugs manually]
→ Re-run tests
→ Done: Working agent
```

### Pattern 4: Agent with Review Loops and HITL Checkpoints

```
User: "Build an agent with human review and feedback loops"
→ Use /hive-concepts (learn event loop, client-facing nodes)
→ Use /hive-create (build structure with feedback edges)
→ Use /hive-patterns (implement client-facing + feedback patterns)
→ Use /hive-test (validate review flows and edge routing)
→ Done: Agent with HITL checkpoints and review loops
```

## Skill Dependencies

```
hive (meta-skill)
    │
    ├── hive-concepts (foundational)
    │   ├── Architecture concepts (event loop, judges)
    │   ├── Node types (event_loop, function)
    │   ├── Edge routing and priority
    │   ├── Tool discovery procedures
    │   └── Workflow overview
    │
    ├── hive-create (procedural)
    │   ├── Creates package structure
    │   ├── Defines goal
    │   ├── Adds nodes (event_loop, function)
    │   ├── Connects edges with priority routing
    │   ├── Finalizes agent class
    │   └── Requires: hive-concepts
    │
    ├── hive-patterns (reference)
    │   ├── Client-facing interaction patterns
    │   ├── Feedback edges and review loops
    │   ├── Judge patterns (implicit, SchemaJudge)
    │   ├── Fan-out/fan-in parallel execution
    │   └── Context management and anti-patterns
    │
    ├── hive-credentials (utility)
    │   ├── Detects missing credentials
    │   ├── Offers auth method choices (Aden OAuth, direct API key)
    │   ├── Stores securely in ~/.hive/credentials
    │   └── Validates with health checks
    │
    ├── hive-test (validation)
    │   ├── Reads agent goal
    │   ├── Generates tests
    │   ├── Runs evaluation
    │   └── Reports results
    │
    └── hive-debugger (troubleshooting)
        ├── Monitors runtime logs (L1/L2/L3)
        ├── Identifies retry loops, tool failures
        ├── Categorizes issues (10 categories)
        └── Provides fix recommendations
```

## Troubleshooting

### "Agent structure won't validate"

- Check node IDs match between nodes/__init__.py and agent.py
- Verify all edges reference valid node IDs
- Ensure entry_node exists in nodes list
- Run: `PYTHONPATH=exports uv run python -m agent_name validate`

### "Agent has structure but won't run"

- Check for STATUS.md or IMPLEMENTATION_GUIDE.md in agent directory
- Implementation may be needed (Python functions or MCP tools)
- This is expected - hive-create creates structure, not implementation
- See implementation guide for completion options

### "Tests are failing"

- Review test output for specific failures
- Check agent goal and success criteria
- Verify constraints are met
- Use `/hive-test` to debug and iterate
- Fix agent code and re-run tests

### "Agent is failing at runtime"

- Use `/hive-debugger` to analyze runtime logs
- The debugger identifies retry loops, tool failures, and stalled execution
- Get actionable fix recommendations with code changes
- Monitor the agent in real-time during TUI sessions

### "Not sure which phase I'm in"

Run these checks:

```bash
# Check if agent structure exists
ls exports/my_agent/agent.py

# Check if it validates
PYTHONPATH=exports uv run python -m my_agent validate

# Check if tests exist
ls exports/my_agent/tests/

# If structure exists and validates → Phase 2 (testing)
# If structure doesn't exist → Phase 1 (building)
# If tests exist but failing → Debug phase
```

## Best Practices

### For Phase 1 (Building)

1. **Start with clear requirements** - Know what the agent should do
2. **Define success criteria early** - Measurable goals drive design
3. **Keep nodes focused** - One responsibility per node
4. **Use descriptive names** - Node IDs should explain purpose
5. **Validate incrementally** - Check structure after each major addition

### For Phase 2 (Testing)

1. **Test constraints first** - Hard requirements must pass
2. **Mock external dependencies** - Use mock mode for LLMs/APIs
3. **Cover edge cases** - Test failures, not just success paths
4. **Iterate quickly** - Fix one test at a time
5. **Document test patterns** - Future tests follow same structure

### General Workflow

1. **Use version control** - Git commit after each phase
2. **Document decisions** - Update README with changes
3. **Keep iterations small** - Build → Test → Fix → Repeat
4. **Preserve working states** - Tag successful iterations
5. **Learn from failures** - Failed tests reveal design issues

## Exit Criteria

You're done with the workflow when:

✅ Agent structure validates
✅ All tests pass
✅ Success criteria met
✅ Constraints verified
✅ Documentation complete
✅ Agent ready for deployment

## Additional Resources

- **hive-concepts**: See `.claude/skills/hive-concepts/SKILL.md`
- **hive-create**: See `.claude/skills/hive-create/SKILL.md`
- **hive-patterns**: See `.claude/skills/hive-patterns/SKILL.md`
- **hive-test**: See `.claude/skills/hive-test/SKILL.md`
- **Agent framework docs**: See `core/README.md`
- **Example agents**: See `exports/` directory

## Summary

This workflow provides a proven path from concept to production-ready agent:

1. **Learn** with `/hive-concepts` → Understand fundamentals (optional)
2. **Build** with `/hive-create` → Get validated structure
3. **Optimize** with `/hive-patterns` → Apply best practices (optional)
4. **Configure** with `/hive-credentials` → Set up API keys (if needed)
5. **Test** with `/hive-test` → Get verified functionality
6. **Debug** with `/hive-debugger` → Fix runtime issues (if needed)

The workflow is **flexible** - skip phases as needed, iterate freely, and adapt to your specific requirements. The goal is **production-ready agents** built with **consistent, repeatable processes**.

## Skill Selection Guide

**Choose hive-concepts when:**
- First time building agents
- Need to understand event loop architecture
- Validating tool availability
- Learning about node types, edges, and judges

**Choose hive-create when:**
- Actually building an agent
- Have clear requirements
- Ready to write code
- Want step-by-step guidance
- Want to start from an existing template and customize it

**Choose hive-patterns when:**
- Agent structure complete
- Need client-facing nodes or feedback edges
- Implementing review loops or fan-out/fan-in
- Want judge patterns or context management
- Want best practices

**Choose hive-test when:**
- Agent structure complete
- Ready to validate functionality
- Need comprehensive test coverage
- Testing feedback loops, output keys, or fan-out

**Choose hive-debugger when:**
- Agent is failing or stuck at runtime
- Seeing retry loops or escalations
- Tool calls are failing
- Need to understand why a node isn't completing
- Want real-time monitoring of agent execution
