By NamhaeSusan
Generate standardized operational agents for any component using deepagents. Analyzes codebase, designs agent via Q&A, generates code, and validates structure.
Create a standardized operational agent for a component — orchestrates the full analyze → design → generate → validate workflow
Analyze a component's codebase to understand its logging, metrics, and infrastructure for ops agent creation
Design an operational agent based on codebase analysis, determining tools, config, and system prompt content
Generate a deepagents-based operational agent project from templates and design document
Run AST guard validation on a generated agent project and auto-fix violations
Claude Code plugin that generates standardized operational agents for any component using deepagents.
Point it at any component's codebase, and it walks you through creating an ops agent that can:
Every generated agent follows the same structure — enforced by an AST guard.
# From Claude Code
/plugin install build-my-agent
In Claude Code, invoke the skill:
> create-ops-agent
Claude will walk you through 4 phases:
cd <component>-ops-agent
pip install -e '.[dev]'
python agent.py
# Interactive chat (default)
python agent.py
# Single query
python agent.py --once "check error rate for the last hour"
# Structured diagnosis (returns JSON DiagnosisReport)
python agent.py --diagnose --once "why is latency high?"
Every agent follows this standard layout:
<component>-ops-agent/
├── pyproject.toml
├── agent.py # Entry point: create_deep_agent()
├── models.py # DiagnosisReport for structured output
├── config/
│ └── agent.yaml # Endpoints, index patterns, namespaces
├── tools/
│ ├── __init__.py
│ ├── log_search.py # OpenSearch log query
│ ├── metric_query.py # Prometheus metric query
│ ├── http_client.py # HTTP requests (health checks, deploy triggers)
│ └── ... # Custom tools (Kafka, DB, etc.)
├── prompts/
│ └── system.md # Domain knowledge for the agent
├── skills/
│ └── troubleshooting/
│ ├── SKILL.md # Troubleshooting index
│ └── runbooks/ # Individual runbook files
│ ├── triage.md
│ └── common-issues.md
└── tests/
├── test_tools.py
└── test_agent.py
tools/ with one public function and a docstringconfig/agent.yamltools/__init__.py and register in agent.pypython -m guard check .The AST guard enforces:
| Rule | Description |
|---|---|
| Structure | Required files and directories must exist |
| Naming | Tool files and functions must be snake_case |
| Pattern | One public function per tool file |
| Pattern | All tool functions must have docstrings |
| Pattern | No hardcoded URLs (must use config) |
| Pattern | Config must be loaded from config/agent.yaml |
| Lint | ruff checks all Python files (E, F, I rules) |
build-my-agent/
├── .claude-plugin/plugin.json # Plugin manifest
├── skills/ # Claude Code skills
│ ├── 00-create-ops-agent/ # Entry point (orchestration)
│ ├── 01-analyze-codebase/ # Phase 1: Analyze
│ ├── 02-design-agent/ # Phase 2: Design
│ ├── 03-generate-agent/ # Phase 3: Generate
│ └── 04-validate-structure/ # Phase 4: Validate
├── guard/ # AST structure validator
├── tools/ # Reference tool implementations
├── templates/ # Agent project boilerplate
└── tests/ # Guard tests
# Run guard tests
python3 -m pytest tests/ -v
# Test guard on a project
python3 -m guard check <agent-project-path>
# Generate a sample agent from templates
python3 scripts/render_agent.py <output-dir>
# Lint
python3 -m ruff check .
MIT
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