Skill Power Tools And Metadata

from pathlib import Path
import sys

ROOT = (
    Path.cwd().resolve().parent
    if Path.cwd().name == "notebooks"
    else Path.cwd().resolve()
)
if str(ROOT) not in sys.path:
    sys.path.insert(0, str(ROOT))

from examples.run_multi_tool_agent import build_llm_from_env
from shipit_agent import Agent, DeepAgent, DEFAULT_SKILLS_PATH, FileSkillRegistry

llm = build_llm_from_env("bedrock")

registry = FileSkillRegistry(DEFAULT_SKILLS_PATH)
print("Catalog path:", DEFAULT_SKILLS_PATH)
print("Total packaged skills:", len(registry.list()))

for skill in registry.search("workflow")[:5]:
    print(f"- {skill.id}: {skill.description}")

agent = Agent.with_builtins(
    llm=llm,
    project_root="/tmp",
    skills=["code-workflow-assistant"],
    auto_use_skills=True,
    skill_match_limit=2,
)

print("Explicit skills attached:")
for skill in agent.skills:
    print("-", skill.id)

scraper_agent = Agent.with_builtins(
    llm=llm,
    project_root="/tmp",
    skills=["web-scraper-pro", "code-workflow-assistant"],
    auto_use_skills=False,
)

tool_names = sorted(
    tool.name for tool in scraper_agent._effective_tools("scrape and patch the parser")
)
for name in tool_names:
    print(name)

prompt = """
We have local work under /tmp.

Please:
1. inspect the scraper code
2. patch the output format if needed
3. save the cleaned result
"""

result = scraper_agent.run(prompt)

print("Used skills:", result.metadata.get("used_skills"))
print("Used skill tools:", result.metadata.get("used_skill_tools"))
print("\nModel output:\n")
print(result.output)

deep_agent = DeepAgent.with_builtins(
    llm=llm,
    project_root="/tmp",
    skills=["web-scraper-pro"],
    default_skill_ids=["code-workflow-assistant"],
    auto_use_skills=True,
    skill_match_limit=2,
)

deep_result = deep_agent.run(
    "Inspect the local scraper under /tmp, fix the slow path, and summarize the changes."
)

print("Used skills:", deep_result.metadata.get("used_skills"))
print("Used skill tools:", deep_result.metadata.get("used_skill_tools"))
print("\nDeepAgent output:\n")
print(getattr(deep_result, "output", str(deep_result)))