Prebuilt agents

from shipit_agent import Agent

analyst  = Agent.for_role("finance-analyst", llm=llm)
writer   = Agent.for_role("marketing-writer", llm=llm)
auditor  = Agent.for_role("security-auditor", llm=llm)

result = analyst.run("Close Q2 and hand me the workbook.")

from shipit_agent import Agent
from shipit_agent.agents import AgentRegistry

registry = AgentRegistry.default()
agent_def = registry.get("security-auditor")

agent = Agent.with_builtins(
    llm=llm,
    prompt=agent_def.system_prompt(),
    max_iterations=agent_def.max_iterations,
)
result = agent.run("Audit my authentication module")

from shipit_agent.agents import AgentRegistry

registry = AgentRegistry.default()
spec = registry.get("code-reviewer-bot")

from shipit_agent import Agent
from shipit_agent.agents import AgentRegistry

spec = AgentRegistry.default().get("code-reviewer-bot")

agent = Agent.with_builtins(
    llm=opus_llm,
    prompt=spec.system_prompt(),
    max_iterations=spec.max_iterations,
)

result = agent.run(
    "Review pull request shipiit/shipit_agent#142. "
    "Comment inline on any issues."
)
print(result.output)

spec = AgentRegistry.default().get("release-engineer")

agent = Agent.with_builtins(
    llm=opus_llm,
    prompt=spec.system_prompt(),
    project_root="/path/to/repo",
)

agent.run(
    "Bump pyproject to 1.1.0, update CHANGELOG with the diff "
    "since v1.0.8, and commit + tag."
)

spec = AgentRegistry.default().get("figma-designer")

agent = Agent.with_builtins(llm=opus_llm, prompt=spec.system_prompt())

agent.run(
    "Open the homepage hero from Figma file abc123, render it, "
    "and post review comments on layout drift from spec."
)

spec = AgentRegistry.default().get("sales-rep")

agent = Agent.with_builtins(llm=opus_llm, prompt=spec.system_prompt())

agent.run(
    "Find 5 senior platform engineers in NYC who worked at Stripe, "
    "log them as leads in Salesforce, and draft a personalised "
    "outreach email for each."
)

spec = AgentRegistry.default().get("account-executive")

agent = Agent.with_builtins(llm=opus_llm, prompt=spec.system_prompt())

agent.run(
    "Review my open opportunities closing this quarter. Flag "
    "anything stalled >14 days and draft a check-in email."
)

spec = AgentRegistry.default().get("sales-ops")

agent = Agent.with_builtins(llm=opus_llm, prompt=spec.system_prompt())

agent.run(
    "Find all leads in Salesforce missing a region tag and "
    "back-fill it from their company HQ in the master Sheets tab."
)

spec = AgentRegistry.default().get("recruiter")

agent = Agent.with_builtins(llm=opus_llm, prompt=spec.system_prompt())

agent.run(
    "Source 10 senior backend engineers in Berlin with Rust + "
    "distributed-systems experience. Public LinkedIn signals only."
)

spec = AgentRegistry.default().get("finance-analyst")

agent = Agent.with_builtins(llm=opus_llm, prompt=spec.system_prompt())

agent.run(
    "Pull last 30d Stripe MRR + churn, cross-reference with the "
    "expense Sheet, and render a one-page cashflow dashboard."
)

spec = AgentRegistry.default().get("customer-support-agent")

agent = Agent.with_builtins(llm=opus_llm, prompt=spec.system_prompt())

agent.run(
    "Triage all unassigned billing tickets in Zendesk. Apply the "
    "right macro, escalate anything mentioning 'fraud' to #ops in Slack."
)

from shipit_agent import Agent, VerifierNetwork
from shipit_agent.agents import AgentRegistry

spec = AgentRegistry.default().get("release-engineer")

agent = Agent.with_builtins(
    llm=opus_llm,
    prompt=spec.system_prompt(),
    verifier=VerifierNetwork(
        llm=haiku_llm,
        goal="Cut a clean release. NO force-pushes. NO history rewrites.",
    ),
)

from shipit_agent import Agent
from shipit_agent.agents import AgentRegistry

registry = AgentRegistry.default()
agent_def = registry.get("security-auditor")

# Point the agent at your project directory
agent = Agent.with_builtins(
    llm=llm,
    prompt=agent_def.system_prompt(),
    project_root="/path/to/my-project",     # agent works inside this directory
    max_iterations=agent_def.max_iterations,
)

result = agent.run("Perform a full security audit of this project. Check for OWASP Top 10 vulnerabilities.")
print(result.output)

agent_def = registry.get("code-reviewer")

agent = Agent.with_builtins(
    llm=llm,
    prompt=agent_def.system_prompt(),
    project_root="/path/to/my-project",
)

result = agent.run("Review the recent changes in src/auth/ for security and code quality issues")
print(result.output)

agent_def = registry.get("architect")

agent = Agent.with_builtins(
    llm=llm,
    prompt=agent_def.system_prompt(),
    project_root="/path/to/my-project",
)

result = agent.run("Review the project architecture. Identify scalability bottlenecks and suggest improvements.")
print(result.output)

agent_def = registry.get("docker-specialist")

agent = Agent.with_builtins(
    llm=llm,
    prompt=agent_def.system_prompt(),
    project_root="/path/to/my-project",
)

result = agent.run("Review the Dockerfiles and docker-compose.yml for optimization and security best practices")
print(result.output)

agent_def = registry.get("security-auditor")

agent = Agent.with_builtins(
    llm=llm,
    prompt=agent_def.system_prompt(),
    project_root="/path/to/my-project",
)

# Watch the agent work in real-time
for event in agent.stream("Scan the entire project for hardcoded secrets and API keys"):
    if event.type == "tool_called":
        tool = event.payload.get("tool_name", "")
        args = str(event.payload.get("arguments", ""))[:100]
        print(f"  🔧 {tool}: {args}")
    elif event.type == "tool_completed":
        print(f"  ✅ {event.payload.get('tool_name', '')} done")
    elif event.type == "run_completed":
        print(f"\n=== Audit Complete ===")
        print(event.payload.get("output", "")[:1000])

# Plain Agent — no file tools, just the LLM + prompt
agent = Agent(
    llm=llm,
    prompt=agent_def.system_prompt(),
    max_iterations=agent_def.max_iterations,
)

result = agent.run("Explain the OWASP Top 10 vulnerabilities and how to prevent each one")

registry = AgentRegistry.default()

# All categories
print(registry.categories())
# ['Architecture', 'Code Quality', 'Content', 'DevOps', 'Planning', 'Research', 'Security', 'Testing']

# List by category
for agent_def in registry.list_by_category("Security"):
    print(f"{agent_def.id}: {agent_def.role}")

results = registry.search("code review python")
for r in results[:5]:
    print(f"{r.id}: {r.role}")

agent_def = registry.get("architect")
print(agent_def.system_prompt())
# # Role
# You are a Software Architect specializing in scalable, maintainable system design.
# 
# # Goal
# Design robust, scalable architectures...
# 
# # Instructions
# When asked to design or review architecture:
# 1. UNDERSTAND THE CONTEXT...

from shipit_agent.agents import AgentDefinition

custom = AgentDefinition(
    id="my-compliance-checker",
    name="Compliance Checker",
    role="Regulatory compliance specialist",
    goal="Check code for GDPR, SOX, and PCI-DSS compliance",
    backstory="Former compliance officer at a Fortune 500 bank.",
    tools=["read_file", "grep_files", "glob_files"],
    prompt="Review code for regulatory compliance...",
    category="Compliance",
    tags=["compliance", "gdpr", "pci"],
)

# Project-local agents override built-in ones with the same ID
builtin = AgentRegistry.default()
project = AgentRegistry([custom])
merged = builtin.merge(project)

.shipit/
  agents/
    my-custom-agent.json
    researcher.json          # overrides built-in "researcher"

local = AgentRegistry.from_directory(".shipit/agents/")
full = AgentRegistry.default().merge(local)

from shipit_agent.deep.ship_crew import ShipAgent

# Load from registry and wrap as ShipAgent
agent = ShipAgent.from_registry("security-auditor", llm=llm)

from shipit_agent.deep import DeepAgent

agent_def = registry.get("researcher")
deep = DeepAgent.with_builtins(
    llm=llm,
    prompt=agent_def.system_prompt(),
    verify=True,
    reflect=True,
)
result = deep.run("Research AI agent security best practices")

agent_def = registry.get("planner")
agent = Agent.with_builtins(llm=llm, prompt=agent_def.system_prompt())

for event in agent.stream("Plan a microservices migration"):
    print(f"[{event.type}] {event.message}")

from shipit_agent import Agent

agent_def = registry.get("code-reviewer")

# Plain Agent — no built-in tools, just the system prompt
agent = Agent(
    llm=llm,
    prompt=agent_def.system_prompt(),
    max_iterations=agent_def.max_iterations,
)

result = agent.run("Review this function for bugs")
print(result.output)

agent_def = registry.get("security-auditor")
agent = Agent(llm=llm, prompt=agent_def.system_prompt())

for event in agent.stream("Check this code for SQL injection"):
    if event.type == "run_started":
        print(f"[START] Agent running...")
    elif event.type == "tool_called":
        print(f"[TOOL]  {event.payload.get('tool_name', 'llm')}")
    elif event.type == "tool_completed":
        print(f"[DONE]  {event.payload.get('tool_name', 'llm')}")
    elif event.type == "run_completed":
        print(f"[END]   Output: {event.payload.get('output', '')[:200]}")

from shipit_agent.deep import DeepAgent

agent_def = registry.get("researcher")

# DeepAgent with verification and reflection
deep = DeepAgent.with_builtins(
    llm=llm,
    prompt=agent_def.system_prompt(),
    verify=True,
    reflect=True,
    max_iterations=12,
)

# Run with full deep agent capabilities
result = deep.run("Research the latest trends in AI agent security")
print(result.output)

# Stream deep agent events
for event in deep.stream("Research quantum computing advances"):
    print(f"[{event.type}] {event.message[:100]}")

from shipit_agent import Agent
from shipit_agent.deep import DeepAgent

# Load prebuilt agents as sub-agents for delegation
researcher_def = registry.get("researcher")
writer_def = registry.get("blog-writer")
reviewer_def = registry.get("code-reviewer")

researcher_agent = Agent(llm=llm, prompt=researcher_def.system_prompt())
writer_agent = Agent(llm=llm, prompt=writer_def.system_prompt())
reviewer_agent = Agent(llm=llm, prompt=reviewer_def.system_prompt())

deep = DeepAgent.with_builtins(
    llm=llm,
    agents=[researcher_agent, writer_agent, reviewer_agent],
)

result = deep.run("Research AI trends, write a blog post, and review it")

# To JSON (camelCase keys)
d = agent_def.to_dict()

# From JSON (accepts camelCase or snake_case)
restored = AgentDefinition.from_dict(d)