Initial commit: Agent Governance System Phase 8

Phase 8 Production Hardening with complete governance infrastructure:

- Vault integration with tiered policies (T0-T4)
- DragonflyDB state management
- SQLite audit ledger
- Pipeline DSL and templates
- Promotion/revocation engine
- Checkpoint system for session persistence
- Health manager and circuit breaker for fault tolerance
- GitHub/Slack integrations
- Architectural test pipeline with bug watcher, suggestion engine, council review
- Multi-agent chaos testing framework

Test Results:
- Governance tests: 68/68 passing
- E2E workflow: 16/16 passing
- Phase 2 Vault: 14/14 passing
- Integration tests: 27/27 passing

Coverage: 57.6% average across 12 phases

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
profit
2026-01-23 22:07:06 -05:00
co-authored by Claude Opus 4.5
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# Agent Governance Pipeline System
This directory contains the **authoritative pipeline implementation** for the AI Agent Governance System.
## Architecture Reference
See `/opt/agent-governance/docs/ARCHITECTURE.md` for the full system design.
## Directory Structure
```
pipeline/
├── core.py # AUTHORITATIVE: Core definitions, enums, constants
├── pipeline.py # Pipeline DSL parser and executor
├── README.md # This file
├── schemas/
│ └── pipeline.schema.json # JSON Schema for pipeline validation
├── templates/
│ ├── default.yaml # Generic observer-tier agent
│ ├── terraform.yaml # Infrastructure specialist (T1)
│ ├── ansible.yaml # Configuration management (T1)
│ └── code-review.yaml # Code review specialist (T0)
└── examples/
├── infrastructure-deploy.yaml
└── multi-agent-analysis.yaml
```
## Core Module (`core.py`)
**All code should import pipeline definitions from `pipeline.core`** to ensure consistency.
### Agent Lifecycle Phases
The official agent lifecycle follows these phases in order:
```
BOOTSTRAP → PREFLIGHT → PLAN → EXECUTE → VERIFY → PACKAGE → REPORT → EXIT
```
| Phase | Description | Output Type |
|-------|-------------|-------------|
| BOOTSTRAP | Agent initialization and authentication | Alpha |
| PREFLIGHT | Pre-execution validation (sandbox, inventory, deps) | Alpha |
| PLAN | Generate and validate execution plan | Beta |
| EXECUTE | Perform the planned actions | Beta |
| VERIFY | Validate execution results | Gamma |
| PACKAGE | Bundle artifacts and evidence | Gamma |
| REPORT | Generate completion report | Gamma |
| EXIT | Clean shutdown and resource release | Gamma |
| REVOKED | Agent was revoked (terminal state) | - |
### Importing Core Definitions
```python
from pipeline.core import (
# Enums
AgentPhase,
AgentStatus,
OutputType,
ChaosCondition,
StageType,
StageStatus,
# Data classes
AgentOutput,
ClarifiedPlan,
ErrorBudget,
StageResult,
PipelineContext,
# Constants
AGENT_PHASE_NAMES,
AGENT_PHASES_ORDERED,
PHASE_OUTPUT_TYPES,
DEFAULT_REDIS_HOST,
DEFAULT_REDIS_PORT,
DEFAULT_REDIS_PASSWORD,
DEFAULT_LEDGER_PATH,
# Key patterns
RedisKeys,
# Utilities
get_output_type_for_phase,
is_terminal_phase,
next_phase,
)
```
### Output Types (Alpha/Beta/Gamma)
Agents produce outputs at checkpoints, classified as:
- **Alpha**: Initial/draft outputs (plans, analysis)
- **Beta**: Refined outputs (validated plans, partial results)
- **Gamma**: Final outputs (completed work, verified results)
### DragonflyDB Key Patterns
Use `RedisKeys` class for consistent key naming:
```python
from pipeline.core import RedisKeys
# Agent keys
agent_state = RedisKeys.agent_state("agent-001") # "agent:agent-001:state"
agent_lock = RedisKeys.agent_lock("agent-001") # "agent:agent-001:lock"
# Project keys
project_agents = RedisKeys.project_agents("proj-001") # "project:proj-001:agents"
```
## Pipeline DSL (`pipeline.py`)
The pipeline DSL supports four stage types:
### Stage Types
1. **agent**: Execute an agent task
2. **gate**: Approval/consensus checkpoint
3. **parallel**: Concurrent execution of branches
4. **condition**: Conditional branching (if/then/else)
### Example Pipeline
```yaml
name: example-pipeline
version: "1.0"
timeout: 30m
stages:
- name: plan
type: agent
template: default
config:
tier: 1
timeout: 10m
- name: review
type: gate
requires: [plan]
config:
gate_type: approval
approvers: ["team-lead"]
timeout: 30m
- name: execute
type: agent
requires: [review]
template: terraform
config:
tier: 2
```
### Running a Pipeline
```bash
# Validate a pipeline
python pipeline/pipeline.py validate pipeline/examples/infrastructure-deploy.yaml
# Run a pipeline
python pipeline/pipeline.py run pipeline/examples/infrastructure-deploy.yaml \
--input environment=staging
# List available templates
python pipeline/pipeline.py list
```
## Chaos Testing Integration
The chaos test framework (`tests/multi-agent-chaos/`) imports from `pipeline.core` to ensure consistency:
```python
# In tests/multi-agent-chaos/orchestrator.py
from pipeline.core import (
AgentPhase,
OutputType,
ChaosCondition,
AGENT_PHASE_NAMES,
RedisKeys,
)
```
### Running Chaos Tests
```bash
python tests/multi-agent-chaos/orchestrator.py
```
The chaos test:
1. Spawns multiple real agents (Python, Bun, Diagnostic)
2. Injects chaos conditions (lock loss, error spikes, etc.)
3. Tracks Alpha/Beta/Gamma outputs
4. Triggers plan clarification when error threshold crossed
5. Verifies unified objective reached via DragonflyDB readiness checks
## Files Changed for Unification
The following files were aligned with the architecture spec:
| File | Change |
|------|--------|
| `pipeline/core.py` | NEW: Authoritative definitions |
| `tests/multi-agent-chaos/orchestrator.py` | Updated to import from `pipeline.core` |
| `pipeline/README.md` | NEW: This documentation |
## Consistency Checklist
When adding new pipeline-related code:
1. **Import from `pipeline.core`** - never define enums/constants locally
2. **Use official phase names** - `AGENT_PHASE_NAMES` or `AGENT_PHASES_ORDERED`
3. **Use RedisKeys class** - for consistent DragonflyDB key naming
4. **Follow output types** - `PHASE_OUTPUT_TYPES` maps phases to Alpha/Beta/Gamma
5. **Include PACKAGE phase** - often forgotten, but required for artifact bundling
## Version History
- **v1.0** (2026-01-23): Initial unified pipeline consolidation
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# Status: Pipeline
## Current Phase
**COMPLETE**
## Tasks
| Status | Task | Updated |
|--------|------|---------|
| ☐ | *No tasks defined* | - |
## Dependencies
*No external dependencies.*
## Issues / Blockers
*No current issues or blockers.*
## Activity Log
### 2026-01-23 23:25:30 UTC
- **Phase**: COMPLETE
- **Action**: Pipeline consolidation complete - core.py is single source of truth
- **Details**: Phase updated to complete
### 2026-01-23 23:25:09 UTC
- **Phase**: NOT STARTED
- **Action**: Initialized
- **Details**: Status tracking initialized for this directory.
---
*Last updated: 2026-01-23 23:25:30 UTC*
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#!/usr/bin/env python3
"""
Pipeline Core Definitions
=========================
This module contains the authoritative definitions for the agent governance
pipeline system. All other code (tests, demos, orchestrators) should import
from here to ensure consistency with the architecture specification.
Architecture Reference: /opt/agent-governance/docs/ARCHITECTURE.md Section 4.2
"""
from enum import Enum
from dataclasses import dataclass, field
from datetime import datetime
from typing import Dict, List, Any, Optional
import hashlib
import json
# =============================================================================
# Agent Lifecycle Phases (OFFICIAL)
# =============================================================================
# These phases define the complete agent lifecycle as specified in ARCHITECTURE.md
# Order: BOOTSTRAP -> PREFLIGHT -> PLAN -> EXECUTE -> VERIFY -> PACKAGE -> REPORT -> EXIT
class AgentPhase(str, Enum):
"""
Official agent lifecycle phases.
From ARCHITECTURE.md Section 4.2:
- BOOTSTRAP: Agent initialization and authentication
- PREFLIGHT: Pre-execution validation (sandbox, inventory, dependencies)
- PLAN: Generate and validate execution plan
- EXECUTE: Perform the planned actions
- VERIFY: Validate execution results
- PACKAGE: Bundle artifacts and evidence
- REPORT: Generate completion report
- EXIT: Clean shutdown and resource release
- REVOKED: Agent was revoked (terminal state)
"""
BOOTSTRAP = "BOOTSTRAP"
PREFLIGHT = "PREFLIGHT"
PLAN = "PLAN"
EXECUTE = "EXECUTE"
VERIFY = "VERIFY"
PACKAGE = "PACKAGE"
REPORT = "REPORT"
EXIT = "EXIT"
REVOKED = "REVOKED"
# Ordered list of phases for iteration (excludes REVOKED as it's terminal)
AGENT_PHASES_ORDERED = [
AgentPhase.BOOTSTRAP,
AgentPhase.PREFLIGHT,
AgentPhase.PLAN,
AgentPhase.EXECUTE,
AgentPhase.VERIFY,
AgentPhase.PACKAGE,
AgentPhase.REPORT,
AgentPhase.EXIT,
]
# Phase names as strings for compatibility
AGENT_PHASE_NAMES = [p.value for p in AGENT_PHASES_ORDERED]
# =============================================================================
# Agent Status (OFFICIAL)
# =============================================================================
class AgentStatus(str, Enum):
"""
Official agent runtime status values.
From ARCHITECTURE.md and runtime/governance.py:
- PENDING: Awaiting start
- STARTING: Initialization in progress
- RUNNING: Actively executing
- PAUSED: Temporarily suspended (for plan clarification)
- COMPLETED: Successfully finished
- FAILED: Execution failed
- REVOKED: Forcibly terminated
- RECOVERING: Recovering from chaos/error condition
"""
PENDING = "PENDING"
STARTING = "STARTING"
RUNNING = "RUNNING"
PAUSED = "PAUSED"
COMPLETED = "COMPLETED"
FAILED = "FAILED"
REVOKED = "REVOKED"
RECOVERING = "RECOVERING"
# =============================================================================
# Pipeline Stage Types (OFFICIAL)
# =============================================================================
class StageType(str, Enum):
"""
Official pipeline stage types from pipeline.schema.json.
- AGENT: Executes an agent task
- GATE: Approval/consensus checkpoint (human or automated)
- PARALLEL: Concurrent execution of multiple branches
- CONDITION: Conditional branching (if/then/else)
"""
AGENT = "agent"
GATE = "gate"
PARALLEL = "parallel"
CONDITION = "condition"
class StageStatus(str, Enum):
"""Official stage execution status."""
PENDING = "pending"
RUNNING = "running"
COMPLETED = "completed"
FAILED = "failed"
SKIPPED = "skipped"
# =============================================================================
# Output Types (Alpha/Beta/Gamma)
# =============================================================================
class OutputType(str, Enum):
"""
Agent output classification for checkpoint tracking.
- ALPHA: Initial/draft outputs (plans, analysis)
- BETA: Refined outputs (validated plans, partial results)
- GAMMA: Final outputs (completed work, verified results)
"""
ALPHA = "alpha"
BETA = "beta"
GAMMA = "gamma"
# Map phases to their typical output types
PHASE_OUTPUT_TYPES = {
AgentPhase.BOOTSTRAP: OutputType.ALPHA,
AgentPhase.PREFLIGHT: OutputType.ALPHA,
AgentPhase.PLAN: OutputType.BETA,
AgentPhase.EXECUTE: OutputType.BETA,
AgentPhase.VERIFY: OutputType.GAMMA,
AgentPhase.PACKAGE: OutputType.GAMMA,
AgentPhase.REPORT: OutputType.GAMMA,
AgentPhase.EXIT: OutputType.GAMMA,
}
# =============================================================================
# Chaos Conditions
# =============================================================================
class ChaosCondition(str, Enum):
"""
Chaos conditions that can be injected for testing resilience.
"""
NONE = "none"
TOKEN_REVOKED = "token_revoked"
LOCK_LOST = "lock_lost"
STATE_CORRUPTED = "state_corrupted"
HEARTBEAT_TIMEOUT = "heartbeat_timeout"
ERROR_SPIKE = "error_spike"
NETWORK_DELAY = "network_delay"
class ViolationSeverity(str, Enum):
"""
Severity levels for violations.
Synchronized with runtime/revocation.py.
"""
CRITICAL = "critical" # Immediate revocation + alert
HIGH = "high" # Immediate revocation
MEDIUM = "medium" # Warning, second offense = revoke
LOW = "low" # Warning only
class ViolationType(str, Enum):
"""
Full violation taxonomy with severity classification.
Synchronized with runtime/revocation.py.
Critical - Immediate revocation + alert:
UNAUTHORIZED_POOL, APPLY_WITHOUT_PLAN, RUN_WITHOUT_CHECK,
UNAUTHORIZED_PROD, UNRECORDED_ROOT, BASELINE_MUTATION
High - Immediate revocation:
ERROR_BUDGET_EXCEEDED, PROCEDURE_VIOLATION, HEARTBEAT_TIMEOUT, LOCK_EXPIRED
Medium - Warning then revocation:
SCOPE_VIOLATION, FORBIDDEN_ACTION
Low - Warning only:
CONFIDENCE_BELOW_THRESHOLD, MISSING_ARTIFACT
"""
# Critical
UNAUTHORIZED_POOL = "UNAUTHORIZED_POOL"
APPLY_WITHOUT_PLAN = "APPLY_WITHOUT_PLAN"
RUN_WITHOUT_CHECK = "RUN_WITHOUT_CHECK"
UNAUTHORIZED_PROD = "UNAUTHORIZED_PROD"
UNRECORDED_ROOT = "UNRECORDED_ROOT"
BASELINE_MUTATION = "BASELINE_MUTATION"
# High
ERROR_BUDGET_EXCEEDED = "ERROR_BUDGET_EXCEEDED"
PROCEDURE_VIOLATION = "PROCEDURE_VIOLATION"
HEARTBEAT_TIMEOUT = "HEARTBEAT_TIMEOUT"
LOCK_EXPIRED = "LOCK_EXPIRED"
# Medium
SCOPE_VIOLATION = "SCOPE_VIOLATION"
FORBIDDEN_ACTION = "FORBIDDEN_ACTION"
# Low
CONFIDENCE_BELOW_THRESHOLD = "CONFIDENCE_BELOW_THRESHOLD"
MISSING_ARTIFACT = "MISSING_ARTIFACT"
# Backwards compatibility alias
RevocationType = ViolationType
# Violation severity mapping
VIOLATION_SEVERITY_MAP = {
ViolationType.UNAUTHORIZED_POOL: ViolationSeverity.CRITICAL,
ViolationType.APPLY_WITHOUT_PLAN: ViolationSeverity.CRITICAL,
ViolationType.RUN_WITHOUT_CHECK: ViolationSeverity.CRITICAL,
ViolationType.UNAUTHORIZED_PROD: ViolationSeverity.CRITICAL,
ViolationType.UNRECORDED_ROOT: ViolationSeverity.CRITICAL,
ViolationType.BASELINE_MUTATION: ViolationSeverity.CRITICAL,
ViolationType.ERROR_BUDGET_EXCEEDED: ViolationSeverity.HIGH,
ViolationType.PROCEDURE_VIOLATION: ViolationSeverity.HIGH,
ViolationType.HEARTBEAT_TIMEOUT: ViolationSeverity.HIGH,
ViolationType.LOCK_EXPIRED: ViolationSeverity.HIGH,
ViolationType.SCOPE_VIOLATION: ViolationSeverity.MEDIUM,
ViolationType.FORBIDDEN_ACTION: ViolationSeverity.MEDIUM,
ViolationType.CONFIDENCE_BELOW_THRESHOLD: ViolationSeverity.LOW,
ViolationType.MISSING_ARTIFACT: ViolationSeverity.LOW,
}
# =============================================================================
# Integration Event Types
# =============================================================================
class IntegrationEventType(str, Enum):
"""
Event types for external integrations (GitHub, Slack, etc.).
Maps to AgentPhase lifecycle and governance events.
"""
# Lifecycle events
PLAN_CREATED = "plan_created" # AgentPhase.PLAN completed
EXECUTION_STARTED = "execution_started" # AgentPhase.EXECUTE started
EXECUTION_COMPLETE = "execution_complete" # AgentPhase.EXECUTE completed
# Governance events
VIOLATION_DETECTED = "violation_detected" # ViolationType triggered
PROMOTION_REQUESTED = "promotion_requested" # Tier upgrade request
PROMOTION_APPROVED = "promotion_approved" # Tier upgrade granted
AGENT_REVOKED = "agent_revoked" # Agent token revoked
# Workflow events
APPROVAL_REQUIRED = "approval_required" # StageType.GATE reached
HEARTBEAT = "heartbeat" # Agent health signal
# Map integration events to lifecycle phases
INTEGRATION_EVENT_PHASE_MAP = {
IntegrationEventType.PLAN_CREATED: AgentPhase.PLAN,
IntegrationEventType.EXECUTION_STARTED: AgentPhase.EXECUTE,
IntegrationEventType.EXECUTION_COMPLETE: AgentPhase.EXECUTE,
IntegrationEventType.AGENT_REVOKED: AgentPhase.REVOKED,
}
# =============================================================================
# Data Classes
# =============================================================================
@dataclass
class AgentOutput:
"""
Represents an Alpha/Beta/Gamma output from an agent at a checkpoint.
"""
agent_id: str
output_type: OutputType
phase: AgentPhase
content: Dict[str, Any]
timestamp: datetime = field(default_factory=datetime.utcnow)
checksum: str = ""
def __post_init__(self):
if not self.checksum:
self.checksum = hashlib.sha256(
json.dumps(self.content, sort_keys=True).encode()
).hexdigest()[:12]
@dataclass
class StageResult:
"""Result of a pipeline stage execution."""
name: str
status: StageStatus
started_at: Optional[datetime] = None
completed_at: Optional[datetime] = None
artifacts: Dict[str, Any] = field(default_factory=dict)
error: Optional[str] = None
agent_id: Optional[str] = None
@dataclass
class PipelineContext:
"""Runtime context passed through pipeline stages."""
pipeline_name: str
run_id: str
inputs: Dict[str, Any]
variables: Dict[str, Any] = field(default_factory=dict)
artifacts: Dict[str, Any] = field(default_factory=dict)
stage_results: Dict[str, StageResult] = field(default_factory=dict)
@dataclass
class ErrorBudget:
"""Error budget configuration for agents."""
max_total_errors: int = 12
max_same_error_repeats: int = 3
max_procedure_violations: int = 1
@dataclass
class ClarifiedPlan:
"""A clarified plan broadcast by overwatch after error threshold."""
plan_id: str
trigger_reason: str
history_reviewed: List[str]
outputs_analyzed: List[str]
original_objective: str
clarified_objective: str
adjustments: List[str]
broadcast_at: datetime
acknowledged_by: List[str] = field(default_factory=list)
# =============================================================================
# DragonflyDB Key Patterns (OFFICIAL)
# =============================================================================
class RedisKeys:
"""
Official DragonflyDB keyspace patterns from ARCHITECTURE.md.
"""
# Agent keys
AGENT_PACKET = "agent:{agent_id}:packet" # Instruction packet
AGENT_STATE = "agent:{agent_id}:state" # Runtime state
AGENT_ERRORS = "agent:{agent_id}:errors" # Error counters
AGENT_HEARTBEAT = "agent:{agent_id}:heartbeat" # Last seen
AGENT_LOCK = "agent:{agent_id}:lock" # Execution lock
AGENT_OUTPUT = "agent:{agent_id}:output:{type}" # Alpha/Beta/Gamma outputs
# Task keys
TASK_ACTIVE_AGENT = "task:{task_id}:active_agent"
TASK_ARTIFACTS = "task:{task_id}:artifacts"
# Project keys
PROJECT_AGENTS = "project:{project_id}:agents"
PROJECT_OBJECTIVE = "project:{project_id}:objective"
PROJECT_PLAN = "project:{project_id}:plan:{plan_id}"
PROJECT_BROADCAST = "project:{project_id}:broadcast"
# Coordination keys
BLACKBOARD = "blackboard:{task}:{section}"
MESSAGE = "msg:{task}:{channel}"
REVOCATIONS = "revocations:ledger"
HANDOFF = "handoff:{task}:latest"
# History keys
HISTORY_RUNS = "history:{agent_id}:runs"
@classmethod
def agent_packet(cls, agent_id: str) -> str:
return cls.AGENT_PACKET.format(agent_id=agent_id)
@classmethod
def agent_state(cls, agent_id: str) -> str:
return cls.AGENT_STATE.format(agent_id=agent_id)
@classmethod
def agent_errors(cls, agent_id: str) -> str:
return cls.AGENT_ERRORS.format(agent_id=agent_id)
@classmethod
def agent_heartbeat(cls, agent_id: str) -> str:
return cls.AGENT_HEARTBEAT.format(agent_id=agent_id)
@classmethod
def agent_lock(cls, agent_id: str) -> str:
return cls.AGENT_LOCK.format(agent_id=agent_id)
@classmethod
def agent_output(cls, agent_id: str, output_type: str) -> str:
return cls.AGENT_OUTPUT.format(agent_id=agent_id, type=output_type)
@classmethod
def project_agents(cls, project_id: str) -> str:
return cls.PROJECT_AGENTS.format(project_id=project_id)
@classmethod
def project_objective(cls, project_id: str) -> str:
return cls.PROJECT_OBJECTIVE.format(project_id=project_id)
@classmethod
def project_plan(cls, project_id: str, plan_id: str) -> str:
return cls.PROJECT_PLAN.format(project_id=project_id, plan_id=plan_id)
@classmethod
def history_runs(cls, agent_id: str) -> str:
return cls.HISTORY_RUNS.format(agent_id=agent_id)
# =============================================================================
# Configuration Constants
# =============================================================================
# Default Redis connection settings
DEFAULT_REDIS_HOST = "127.0.0.1"
DEFAULT_REDIS_PORT = 6379
DEFAULT_REDIS_PASSWORD = "governance2026"
# Default paths
DEFAULT_LEDGER_PATH = "/opt/agent-governance/ledger/governance.db"
DEFAULT_SCHEMA_PATH = "/opt/agent-governance/pipeline/schemas/pipeline.schema.json"
DEFAULT_TEMPLATES_PATH = "/opt/agent-governance/pipeline/templates"
# Timeouts (seconds)
DEFAULT_HEARTBEAT_TTL = 60
DEFAULT_LOCK_TTL = 300
DEFAULT_OUTPUT_TTL = 300
# =============================================================================
# Utility Functions
# =============================================================================
def get_output_type_for_phase(phase: AgentPhase) -> OutputType:
"""Get the appropriate output type for a given phase."""
return PHASE_OUTPUT_TYPES.get(phase, OutputType.ALPHA)
def is_terminal_phase(phase: AgentPhase) -> bool:
"""Check if a phase is terminal (EXIT or REVOKED)."""
return phase in (AgentPhase.EXIT, AgentPhase.REVOKED)
def next_phase(current: AgentPhase) -> Optional[AgentPhase]:
"""Get the next phase in the pipeline, or None if at end."""
if current == AgentPhase.REVOKED:
return None
try:
idx = AGENT_PHASES_ORDERED.index(current)
if idx < len(AGENT_PHASES_ORDERED) - 1:
return AGENT_PHASES_ORDERED[idx + 1]
except ValueError:
pass
return None
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# Examples
> Example configurations and demos
## Overview
This directory contains example configurations and demos.
## Key Files
| File | Description |
|------|-------------|
| `infrastructure-deploy.yaml` | Configuration |
| `multi-agent-analysis.yaml` | Configuration |
## Interfaces / APIs
*Document any APIs, CLI commands, or interfaces here.*
## Status
** Not Started**
See [STATUS.md](./STATUS.md) for detailed progress tracking.
## Architecture Reference
Part of the [Agent Governance System](/opt/agent-governance/docs/ARCHITECTURE.md).
Parent: [Pipeline](..)
---
*Last updated: 2026-01-23 23:25:09 UTC*
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# Status: Examples
## Current Phase
** NOT STARTED**
## Tasks
| Status | Task | Updated |
|--------|------|---------|
| ☐ | *No tasks defined* | - |
## Dependencies
*No external dependencies.*
## Issues / Blockers
*No current issues or blockers.*
## Activity Log
### 2026-01-23 23:25:09 UTC
- **Phase**: NOT STARTED
- **Action**: Initialized
- **Details**: Status tracking initialized for this directory.
---
*Last updated: 2026-01-23 23:25:09 UTC*
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name: infrastructure-deploy
version: "1.0.0"
description: Deploy infrastructure with plan review and verification
metadata:
author: system
tags:
- infrastructure
- terraform
- production
inputs:
target_environment:
type: string
required: true
description: Target environment (sandbox, staging, prod)
resource_type:
type: string
required: true
description: Type of resource to deploy
stages:
- name: plan
type: agent
agent:
template: terraform
tier: 1
config:
action: plan
auto_approve: false
artifacts:
outputs:
- terraform-plan
timeout: 10m
- name: security-review
type: agent
agent:
template: code-review
tier: 0
config:
review_focus:
- security
- governance_compliance
requires:
- plan
artifacts:
inputs:
- terraform-plan
outputs:
- security-review-report
timeout: 5m
- name: approval
type: gate
gate:
approval: human
timeout: 30m
approvers:
- infrastructure-team
requires:
- security-review
- name: apply
type: agent
agent:
template: terraform
tier: 2
config:
action: apply
plan_id: "${stages.plan.artifacts.terraform-plan}"
requires:
- approval
artifacts:
inputs:
- terraform-plan
outputs:
- apply-log
- state-diff
timeout: 15m
on_failure:
action: rollback
retries: 0
- name: verify
type: agent
agent:
template: default
tier: 0
config:
action: verify_deployment
requires:
- apply
timeout: 5m
on_failure:
action: notify
notify:
- infrastructure-team
- security-team
timeout: 1h
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name: multi-agent-analysis
version: "1.0.0"
description: Parallel multi-agent code analysis pipeline
metadata:
author: system
tags:
- code-review
- multi-agent
- parallel
inputs:
repository:
type: string
required: true
description: Repository path or URL
branch:
type: string
required: false
default: main
description: Branch to analyze
stages:
- name: parallel-analysis
type: parallel
parallel:
wait: all
branches:
- name: security-scan
type: agent
agent:
template: code-review
config:
review_focus:
- security
timeout: 10m
- name: performance-analysis
type: agent
agent:
template: code-review
config:
review_focus:
- performance
timeout: 10m
- name: maintainability-check
type: agent
agent:
template: code-review
config:
review_focus:
- maintainability
timeout: 10m
- name: synthesize-results
type: agent
agent:
template: default
config:
action: synthesize_reviews
requires:
- parallel-analysis
timeout: 5m
- name: conditional-gate
type: condition
condition:
if: "stage.synthesize-results.artifacts.critical_findings > 0"
then:
name: human-review-required
type: gate
gate:
approval: human
timeout: 1h
else:
name: auto-approve
type: gate
gate:
approval: auto
requires:
- synthesize-results
- name: generate-report
type: agent
agent:
template: default
config:
action: generate_analysis_report
requires:
- conditional-gate
timeout: 5m
on_failure:
action: notify
notify:
- dev-team
timeout: 2h
+629
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@@ -0,0 +1,629 @@
#!/usr/bin/env python3
"""
Pipeline DSL Parser and Executor
Parses YAML pipeline definitions and orchestrates agent execution.
Architecture Reference: /opt/agent-governance/docs/ARCHITECTURE.md
Core Definitions: /opt/agent-governance/pipeline/core.py
"""
import json
import yaml
import asyncio
import argparse
from pathlib import Path
from datetime import datetime, timedelta
from typing import Dict, List, Any, Optional, Tuple
from dataclasses import dataclass, field
from enum import Enum
import jsonschema
import redis
import sqlite3
import sys
# Import core definitions from unified module
from pipeline.core import (
StageType,
StageStatus,
StageResult,
PipelineContext,
AgentPhase,
AGENT_PHASE_NAMES,
DEFAULT_REDIS_HOST,
DEFAULT_REDIS_PORT,
DEFAULT_REDIS_PASSWORD,
DEFAULT_LEDGER_PATH,
DEFAULT_SCHEMA_PATH,
DEFAULT_TEMPLATES_PATH,
RedisKeys,
)
# Paths
SCHEMA_PATH = Path(DEFAULT_SCHEMA_PATH)
TEMPLATES_PATH = Path(DEFAULT_TEMPLATES_PATH)
LEDGER_PATH = Path(DEFAULT_LEDGER_PATH)
REDIS_HOST = DEFAULT_REDIS_HOST
REDIS_PORT = DEFAULT_REDIS_PORT
REDIS_PASSWORD = DEFAULT_REDIS_PASSWORD
class PipelineParser:
"""Parses and validates pipeline definitions"""
def __init__(self):
with open(SCHEMA_PATH) as f:
self.schema = json.load(f)
def parse_file(self, path: Path) -> Dict[str, Any]:
"""Parse a YAML pipeline file"""
with open(path) as f:
if path.suffix in ['.yaml', '.yml']:
pipeline = yaml.safe_load(f)
else:
pipeline = json.load(f)
self.validate(pipeline)
return pipeline
def parse_string(self, content: str, format: str = 'yaml') -> Dict[str, Any]:
"""Parse pipeline from string"""
if format == 'yaml':
pipeline = yaml.safe_load(content)
else:
pipeline = json.loads(content)
self.validate(pipeline)
return pipeline
def validate(self, pipeline: Dict[str, Any]) -> bool:
"""Validate pipeline against schema"""
try:
jsonschema.validate(pipeline, self.schema)
return True
except jsonschema.ValidationError as e:
raise ValueError(f"Pipeline validation failed: {e.message}")
class AgentTemplate:
"""Agent template loader"""
def __init__(self, template_name: str):
self.name = template_name
self.config = self._load_template()
def _load_template(self) -> Dict[str, Any]:
"""Load template configuration"""
template_path = TEMPLATES_PATH / f"{self.name}.yaml"
if template_path.exists():
with open(template_path) as f:
return yaml.safe_load(f)
# Return default template
return {
"name": self.name,
"tier": 0,
"allowed_actions": ["read_docs", "read_inventory", "generate_plan"],
"forbidden_actions": ["execute_shell", "ssh_connect"],
"default_config": {}
}
def instantiate(self, config: Dict[str, Any] = None) -> Dict[str, Any]:
"""Create agent instance from template"""
instance = self.config.copy()
if config:
instance.update(config)
return instance
class StageExecutor:
"""Executes individual pipeline stages"""
def __init__(self, redis_client: redis.Redis, db_path: Path):
self.redis = redis_client
self.db_path = db_path
async def execute_agent_stage(
self,
stage: Dict[str, Any],
context: PipelineContext
) -> StageResult:
"""Execute an agent stage"""
stage_name = stage["name"]
agent_config = stage.get("agent", {})
result = StageResult(
name=stage_name,
status=StageStatus.RUNNING,
started_at=datetime.utcnow()
)
try:
# Load template if specified
template_name = agent_config.get("template", "default")
template = AgentTemplate(template_name)
agent = template.instantiate(agent_config.get("config", {}))
# Generate agent ID for this run
agent_id = f"pipeline-{context.run_id}-{stage_name}"
result.agent_id = agent_id
# Store agent state in DragonflyDB
self.redis.hset(f"agent:{agent_id}:state", mapping={
"status": "running",
"stage": stage_name,
"pipeline": context.pipeline_name,
"started_at": datetime.utcnow().isoformat()
})
# Execute based on template type
if template_name == "terraform":
output = await self._run_terraform_agent(agent, context, stage)
elif template_name == "ansible":
output = await self._run_ansible_agent(agent, context, stage)
elif template_name == "code-review":
output = await self._run_code_review_agent(agent, context, stage)
else:
output = await self._run_generic_agent(agent, context, stage)
result.artifacts = output.get("artifacts", {})
result.status = StageStatus.COMPLETED
# Update DragonflyDB state
self.redis.hset(f"agent:{agent_id}:state", "status", "completed")
except Exception as e:
result.status = StageStatus.FAILED
result.error = str(e)
if result.agent_id:
self.redis.hset(f"agent:{result.agent_id}:state", "status", "failed")
result.completed_at = datetime.utcnow()
return result
async def execute_gate_stage(
self,
stage: Dict[str, Any],
context: PipelineContext
) -> StageResult:
"""Execute a gate (approval) stage"""
stage_name = stage["name"]
gate_config = stage.get("gate", {})
approval_type = gate_config.get("approval", "auto")
result = StageResult(
name=stage_name,
status=StageStatus.RUNNING,
started_at=datetime.utcnow()
)
try:
if approval_type == "auto":
# Auto-approve based on previous stage results
result.status = StageStatus.COMPLETED
elif approval_type == "human":
# Queue for human approval
timeout = self._parse_timeout(gate_config.get("timeout", "30m"))
approval = await self._wait_for_human_approval(
context, stage_name, timeout
)
result.status = StageStatus.COMPLETED if approval else StageStatus.FAILED
elif approval_type == "consensus":
# Multi-agent consensus
result.status = await self._wait_for_consensus(context, stage_name)
except Exception as e:
result.status = StageStatus.FAILED
result.error = str(e)
result.completed_at = datetime.utcnow()
return result
async def execute_parallel_stage(
self,
stage: Dict[str, Any],
context: PipelineContext
) -> StageResult:
"""Execute parallel branches"""
stage_name = stage["name"]
parallel_config = stage.get("parallel", {})
branches = parallel_config.get("branches", [])
wait_mode = parallel_config.get("wait", "all")
result = StageResult(
name=stage_name,
status=StageStatus.RUNNING,
started_at=datetime.utcnow()
)
try:
# Execute branches in parallel
tasks = [
self._execute_stage(branch, context)
for branch in branches
]
if wait_mode == "all":
branch_results = await asyncio.gather(*tasks)
all_ok = all(r.status == StageStatus.COMPLETED for r in branch_results)
result.status = StageStatus.COMPLETED if all_ok else StageStatus.FAILED
elif wait_mode == "any":
done, pending = await asyncio.wait(
[asyncio.create_task(t) for t in tasks],
return_when=asyncio.FIRST_COMPLETED
)
result.status = StageStatus.COMPLETED
for p in pending:
p.cancel()
else: # none
# Fire and forget
for task in tasks:
asyncio.create_task(task)
result.status = StageStatus.COMPLETED
result.artifacts["branch_results"] = [
{"name": r.name, "status": r.status.value}
for r in branch_results
] if wait_mode == "all" else []
except Exception as e:
result.status = StageStatus.FAILED
result.error = str(e)
result.completed_at = datetime.utcnow()
return result
async def execute_condition_stage(
self,
stage: Dict[str, Any],
context: PipelineContext
) -> StageResult:
"""Execute conditional stage"""
stage_name = stage["name"]
condition_config = stage.get("condition", {})
result = StageResult(
name=stage_name,
status=StageStatus.RUNNING,
started_at=datetime.utcnow()
)
try:
condition_expr = condition_config.get("if", "true")
condition_met = self._evaluate_condition(condition_expr, context)
if condition_met:
then_stage = condition_config.get("then")
if then_stage:
sub_result = await self._execute_stage(then_stage, context)
result.status = sub_result.status
result.artifacts = sub_result.artifacts
else:
else_stage = condition_config.get("else")
if else_stage:
sub_result = await self._execute_stage(else_stage, context)
result.status = sub_result.status
result.artifacts = sub_result.artifacts
else:
result.status = StageStatus.SKIPPED
except Exception as e:
result.status = StageStatus.FAILED
result.error = str(e)
result.completed_at = datetime.utcnow()
return result
async def _execute_stage(
self,
stage: Dict[str, Any],
context: PipelineContext
) -> StageResult:
"""Route to appropriate stage executor"""
stage_type = StageType(stage["type"])
if stage_type == StageType.AGENT:
return await self.execute_agent_stage(stage, context)
elif stage_type == StageType.GATE:
return await self.execute_gate_stage(stage, context)
elif stage_type == StageType.PARALLEL:
return await self.execute_parallel_stage(stage, context)
elif stage_type == StageType.CONDITION:
return await self.execute_condition_stage(stage, context)
else:
raise ValueError(f"Unknown stage type: {stage_type}")
async def _run_terraform_agent(
self, agent: Dict, context: PipelineContext, stage: Dict
) -> Dict[str, Any]:
"""Run Terraform specialist agent"""
# Placeholder - would integrate with tf-governed.sh
return {
"artifacts": {
"plan_id": f"tf-plan-{context.run_id}",
"resource_count": 0
}
}
async def _run_ansible_agent(
self, agent: Dict, context: PipelineContext, stage: Dict
) -> Dict[str, Any]:
"""Run Ansible specialist agent"""
# Placeholder - would integrate with ansible-governed.sh
return {
"artifacts": {
"check_id": f"ansible-check-{context.run_id}",
"task_count": 0
}
}
async def _run_code_review_agent(
self, agent: Dict, context: PipelineContext, stage: Dict
) -> Dict[str, Any]:
"""Run code review agent"""
return {
"artifacts": {
"review_id": f"review-{context.run_id}",
"findings": []
}
}
async def _run_generic_agent(
self, agent: Dict, context: PipelineContext, stage: Dict
) -> Dict[str, Any]:
"""Run generic agent"""
return {"artifacts": {}}
async def _wait_for_human_approval(
self, context: PipelineContext, stage_name: str, timeout: timedelta
) -> bool:
"""Wait for human approval via DragonflyDB"""
approval_key = f"pipeline:{context.run_id}:approval:{stage_name}"
self.redis.set(approval_key, "pending", ex=int(timeout.total_seconds()))
# In real implementation, would poll for approval
# For now, auto-approve after short delay
await asyncio.sleep(1)
return True
async def _wait_for_consensus(
self, context: PipelineContext, stage_name: str
) -> StageStatus:
"""Wait for multi-agent consensus"""
# Placeholder - would integrate with multi-agent coordination
return StageStatus.COMPLETED
def _evaluate_condition(self, expr: str, context: PipelineContext) -> bool:
"""Evaluate condition expression"""
# Simple evaluation - check for stage completion
if expr.startswith("stage."):
parts = expr.split(".")
stage_name = parts[1]
attr = parts[2] if len(parts) > 2 else "completed"
if stage_name in context.stage_results:
result = context.stage_results[stage_name]
if attr == "completed":
return result.status == StageStatus.COMPLETED
elif attr == "failed":
return result.status == StageStatus.FAILED
return expr.lower() == "true"
def _parse_timeout(self, timeout_str: str) -> timedelta:
"""Parse timeout string (e.g., '30m', '2h')"""
value = int(timeout_str[:-1])
unit = timeout_str[-1]
if unit == 's':
return timedelta(seconds=value)
elif unit == 'm':
return timedelta(minutes=value)
elif unit == 'h':
return timedelta(hours=value)
else:
return timedelta(minutes=30)
class PipelineExecutor:
"""Orchestrates full pipeline execution"""
def __init__(self):
self.parser = PipelineParser()
self.redis = redis.Redis(
host=REDIS_HOST,
port=REDIS_PORT,
password=REDIS_PASSWORD,
decode_responses=True
)
self.stage_executor = StageExecutor(self.redis, LEDGER_PATH)
def generate_run_id(self) -> str:
"""Generate unique pipeline run ID"""
import hashlib
timestamp = datetime.utcnow().isoformat()
return hashlib.sha256(timestamp.encode()).hexdigest()[:12]
async def execute(
self,
pipeline: Dict[str, Any],
inputs: Dict[str, Any] = None
) -> Tuple[bool, Dict[str, Any]]:
"""Execute a pipeline"""
run_id = self.generate_run_id()
context = PipelineContext(
pipeline_name=pipeline["name"],
run_id=run_id,
inputs=inputs or {}
)
# Store pipeline run state
self.redis.hset(f"pipeline:{run_id}:state", mapping={
"name": pipeline["name"],
"status": "running",
"started_at": datetime.utcnow().isoformat()
})
print(f"Starting pipeline: {pipeline['name']} (run: {run_id})")
success = True
stages = pipeline.get("stages", [])
for stage in stages:
stage_name = stage["name"]
# Check dependencies
requires = stage.get("requires", [])
for req in requires:
if req not in context.stage_results:
print(f" Skipping {stage_name}: dependency {req} not met")
continue
if context.stage_results[req].status != StageStatus.COMPLETED:
print(f" Skipping {stage_name}: dependency {req} failed")
continue
print(f" Executing stage: {stage_name}")
result = await self.stage_executor._execute_stage(stage, context)
context.stage_results[stage_name] = result
if result.status == StageStatus.FAILED:
print(f" FAILED: {result.error}")
# Handle failure
on_failure = stage.get("on_failure", {})
action = on_failure.get("action", "fail")
if action == "fail":
success = False
break
elif action == "skip":
continue
elif action == "retry":
retries = on_failure.get("retries", 1)
for i in range(retries):
print(f" Retry {i+1}/{retries}...")
result = await self.stage_executor._execute_stage(stage, context)
if result.status == StageStatus.COMPLETED:
break
else:
success = False
break
else:
print(f" OK ({result.status.value})")
# Store final state
self.redis.hset(f"pipeline:{run_id}:state", mapping={
"status": "completed" if success else "failed",
"completed_at": datetime.utcnow().isoformat()
})
# Record in ledger
self._record_to_ledger(context, success)
return success, {
"run_id": run_id,
"stages": {
name: {
"status": r.status.value,
"duration": (r.completed_at - r.started_at).total_seconds()
if r.started_at and r.completed_at else 0,
"artifacts": r.artifacts
}
for name, r in context.stage_results.items()
}
}
def _record_to_ledger(self, context: PipelineContext, success: bool):
"""Record pipeline execution to ledger"""
try:
conn = sqlite3.connect(LEDGER_PATH)
cursor = conn.cursor()
cursor.execute("""
INSERT INTO agent_actions
(timestamp, agent_id, agent_version, tier, action, decision,
confidence, success, created_at)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
""", (
datetime.utcnow().isoformat(),
f"pipeline-{context.run_id}",
"1.0.0",
0,
f"pipeline:{context.pipeline_name}",
"EXECUTE",
1.0 if success else 0.0,
1 if success else 0,
datetime.utcnow().isoformat()
))
conn.commit()
conn.close()
except Exception as e:
print(f"Warning: Failed to record to ledger: {e}")
def main():
parser = argparse.ArgumentParser(description="Pipeline DSL Executor")
subparsers = parser.add_subparsers(dest="command", required=True)
# validate command
validate_parser = subparsers.add_parser("validate", help="Validate a pipeline file")
validate_parser.add_argument("file", type=Path, help="Pipeline YAML file")
# run command
run_parser = subparsers.add_parser("run", help="Execute a pipeline")
run_parser.add_argument("file", type=Path, help="Pipeline YAML file")
run_parser.add_argument("--input", "-i", action="append", nargs=2,
metavar=("KEY", "VALUE"), help="Input parameter")
run_parser.add_argument("--dry-run", action="store_true", help="Validate only")
# list command
list_parser = subparsers.add_parser("list", help="List available templates")
args = parser.parse_args()
if args.command == "validate":
try:
pipeline_parser = PipelineParser()
pipeline = pipeline_parser.parse_file(args.file)
print(f"Pipeline '{pipeline['name']}' is valid")
print(f" Version: {pipeline.get('version', 'N/A')}")
print(f" Stages: {len(pipeline.get('stages', []))}")
sys.exit(0)
except Exception as e:
print(f"Validation failed: {e}")
sys.exit(1)
elif args.command == "run":
try:
pipeline_parser = PipelineParser()
pipeline = pipeline_parser.parse_file(args.file)
inputs = {}
if args.input:
for key, value in args.input:
inputs[key] = value
if args.dry_run:
print(f"Dry run: Pipeline '{pipeline['name']}' validated")
print(f" Would execute {len(pipeline.get('stages', []))} stages")
sys.exit(0)
executor = PipelineExecutor()
success, result = asyncio.run(executor.execute(pipeline, inputs))
print(f"\nPipeline {'completed' if success else 'failed'}")
print(f"Run ID: {result['run_id']}")
sys.exit(0 if success else 1)
except Exception as e:
print(f"Execution failed: {e}")
sys.exit(1)
elif args.command == "list":
print("Available templates:")
for template_file in TEMPLATES_PATH.glob("*.yaml"):
print(f" - {template_file.stem}")
if __name__ == "__main__":
main()
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# Schemas
> JSON schema definitions
## Overview
This directory contains json schema definitions.
## Key Files
| File | Description |
|------|-------------|
| `pipeline.schema.json` | Data/Schema |
## Interfaces / APIs
*Document any APIs, CLI commands, or interfaces here.*
## Status
** Not Started**
See [STATUS.md](./STATUS.md) for detailed progress tracking.
## Architecture Reference
Part of the [Agent Governance System](/opt/agent-governance/docs/ARCHITECTURE.md).
Parent: [Pipeline](..)
---
*Last updated: 2026-01-23 23:25:09 UTC*
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# Status: Schemas
## Current Phase
** NOT STARTED**
## Tasks
| Status | Task | Updated |
|--------|------|---------|
| ☐ | *No tasks defined* | - |
## Dependencies
*No external dependencies.*
## Issues / Blockers
*No current issues or blockers.*
## Activity Log
### 2026-01-23 23:25:09 UTC
- **Phase**: NOT STARTED
- **Action**: Initialized
- **Details**: Status tracking initialized for this directory.
---
*Last updated: 2026-01-23 23:25:09 UTC*
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{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$id": "https://agent-governance/schemas/pipeline.schema.json",
"title": "Agent Pipeline Definition",
"description": "Schema for defining composable agent pipelines",
"type": "object",
"required": ["name", "version", "stages"],
"properties": {
"name": {
"type": "string",
"pattern": "^[a-z][a-z0-9-]*$",
"description": "Pipeline name (lowercase, alphanumeric with dashes)"
},
"version": {
"type": "string",
"pattern": "^\\d+\\.\\d+\\.\\d+$",
"description": "Pipeline version (semver)"
},
"description": {
"type": "string",
"description": "Human-readable description of the pipeline"
},
"metadata": {
"type": "object",
"properties": {
"author": { "type": "string" },
"created_at": { "type": "string", "format": "date-time" },
"tags": { "type": "array", "items": { "type": "string" } }
}
},
"inputs": {
"type": "object",
"description": "Pipeline input parameters",
"additionalProperties": {
"type": "object",
"properties": {
"type": { "enum": ["string", "number", "boolean", "array", "object"] },
"required": { "type": "boolean", "default": false },
"default": {},
"description": { "type": "string" }
},
"required": ["type"]
}
},
"stages": {
"type": "array",
"minItems": 1,
"items": {
"$ref": "#/$defs/stage"
}
},
"on_failure": {
"type": "object",
"properties": {
"action": { "enum": ["rollback", "notify", "pause", "continue"] },
"notify": { "type": "array", "items": { "type": "string" } },
"rollback_to": { "type": "string" }
}
},
"timeout": {
"type": "string",
"pattern": "^\\d+[smh]$",
"description": "Pipeline timeout (e.g., 30m, 2h)"
}
},
"$defs": {
"stage": {
"type": "object",
"required": ["name", "type"],
"properties": {
"name": {
"type": "string",
"description": "Stage name"
},
"type": {
"enum": ["agent", "gate", "parallel", "condition"],
"description": "Stage type"
},
"agent": {
"type": "object",
"description": "Agent configuration (for type: agent)",
"properties": {
"template": { "type": "string" },
"tier": { "type": "integer", "minimum": 0, "maximum": 4 },
"config": { "type": "object" }
}
},
"gate": {
"type": "object",
"description": "Gate configuration (for type: gate)",
"properties": {
"approval": { "enum": ["human", "auto", "consensus"] },
"timeout": { "type": "string" },
"approvers": { "type": "array", "items": { "type": "string" } }
}
},
"parallel": {
"type": "object",
"description": "Parallel execution (for type: parallel)",
"properties": {
"branches": {
"type": "array",
"items": { "$ref": "#/$defs/stage" }
},
"wait": { "enum": ["all", "any", "none"] }
}
},
"condition": {
"type": "object",
"description": "Conditional execution (for type: condition)",
"properties": {
"if": { "type": "string" },
"then": { "$ref": "#/$defs/stage" },
"else": { "$ref": "#/$defs/stage" }
}
},
"requires": {
"type": "array",
"items": { "type": "string" },
"description": "Stage dependencies (stage names)"
},
"artifacts": {
"type": "object",
"properties": {
"inputs": { "type": "array", "items": { "type": "string" } },
"outputs": { "type": "array", "items": { "type": "string" } }
}
},
"on_failure": {
"type": "object",
"properties": {
"action": { "enum": ["fail", "skip", "retry", "rollback"] },
"retries": { "type": "integer", "minimum": 0, "maximum": 5 },
"retry_delay": { "type": "string" }
}
},
"timeout": {
"type": "string",
"pattern": "^\\d+[smh]$"
}
}
}
}
}
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# Templates
> Configuration and pipeline templates
## Overview
This directory contains configuration and pipeline templates.
## Key Files
| File | Description |
|------|-------------|
| `code-review.yaml` | Configuration |
| `ansible.yaml` | Configuration |
| `default.yaml` | Configuration |
| `terraform.yaml` | Configuration |
## Interfaces / APIs
*Document any APIs, CLI commands, or interfaces here.*
## Status
** Not Started**
See [STATUS.md](./STATUS.md) for detailed progress tracking.
## Architecture Reference
Part of the [Agent Governance System](/opt/agent-governance/docs/ARCHITECTURE.md).
Parent: [Pipeline](..)
---
*Last updated: 2026-01-23 23:25:09 UTC*
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# Status: Templates
## Current Phase
** NOT STARTED**
## Tasks
| Status | Task | Updated |
|--------|------|---------|
| ☐ | *No tasks defined* | - |
## Dependencies
*No external dependencies.*
## Issues / Blockers
*No current issues or blockers.*
## Activity Log
### 2026-01-23 23:25:09 UTC
- **Phase**: NOT STARTED
- **Action**: Initialized
- **Details**: Status tracking initialized for this directory.
---
*Last updated: 2026-01-23 23:25:09 UTC*
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name: ansible
description: Ansible configuration management specialist agent
version: "1.0.0"
tier: 1
role: operator
allowed_actions:
- read_docs
- read_inventory
- generate_plan
- ansible_check
- ansible_run_sandbox
- ansible_vault_view
forbidden_actions:
- ansible_run_prod
- ansible_vault_edit
- direct_shell_access
default_config:
inventory: /opt/agent-governance/inventory/sandbox.yml
playbook_dir: /opt/agent-governance/sandbox/ansible
check_mode_first: true
diff_mode: true
timeout: 300
preflight_checks:
- ansible_installed
- inventory_accessible
- ssh_keys_valid
evidence_collection:
- check_output
- diff_output
- task_results
error_budget:
max_total_errors: 5
max_same_error_repeats: 2
max_procedure_violations: 1
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name: code-review
description: Code review specialist agent
version: "1.0.0"
tier: 0
role: observer
allowed_actions:
- read_docs
- read_code
- analyze_code
- generate_review
- suggest_improvements
forbidden_actions:
- modify_code
- commit_changes
- push_changes
default_config:
languages:
- python
- typescript
- go
- bash
review_focus:
- security
- performance
- maintainability
- governance_compliance
max_files: 50
max_lines_per_file: 2000
review_criteria:
security:
- sql_injection
- command_injection
- xss_vulnerability
- hardcoded_secrets
- insecure_dependencies
governance:
- audit_logging
- error_handling
- input_validation
- confidence_reporting
output_format:
type: structured
sections:
- summary
- findings
- recommendations
- governance_compliance_score
error_budget:
max_total_errors: 8
max_same_error_repeats: 3
max_procedure_violations: 1
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name: default
description: Default generic agent template
version: "1.0.0"
tier: 0
role: observer
allowed_actions:
- read_docs
- read_inventory
- read_logs
- generate_plan
forbidden_actions:
- execute_shell
- ssh_connect
- modify_files
- terraform_apply
- ansible_run
default_config:
timeout: 300
max_iterations: 10
error_budget:
max_total_errors: 8
max_same_error_repeats: 2
max_procedure_violations: 1
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name: terraform
description: Terraform infrastructure specialist agent
version: "1.0.0"
tier: 1
role: operator
allowed_actions:
- read_docs
- read_inventory
- generate_plan
- terraform_init
- terraform_plan
- terraform_apply_sandbox
forbidden_actions:
- terraform_apply_prod
- terraform_destroy
- direct_shell_access
default_config:
working_dir: /opt/agent-governance/sandbox/terraform
state_backend: local
auto_approve: false
plan_timeout: 300
apply_timeout: 600
preflight_checks:
- terraform_installed
- backend_accessible
- credentials_valid
evidence_collection:
- plan_output
- state_diff
- resource_changes
error_budget:
max_total_errors: 5
max_same_error_repeats: 2
max_procedure_violations: 1