Skill Lifecycle

from praisonaiagents import Agent

agent = Agent(
    name="Self-Improving Agent",
    instructions="Create skills when you learn something new; archive stale ones.",
    tools=["skill_manage", "skills_list"],
)
agent.start("Learn how to summarise weekly reports, then save that as a skill.")

from praisonaiagents import SkillManager

mgr = SkillManager()
mgr.discover()

skill = mgr.get_skill("csv-analysis")
days = skill.properties.idle_days
# Returns days since last_used, or since created_at if the skill has never been used.
# Returns None when neither last_used nor created_at is set.

if days is not None and days > 30:
    print(f"csv-analysis has been idle for {days:.1f} days — consider archiving")

~/.praisonai/
├── skills/               # active skills
│   ├── csv-analysis/
│   │   ├── SKILL.md
│   │   └── .skill.bak    # rollback snapshot (after edit/patch)
│   └── weekly-summary/
│       └── SKILL.md
└── skills_archive/       # archived skills (sibling of skills/)
    ├── csv-analysis/
    └── old-formatter.20240624153012/  # collision-suffixed

from praisonaiagents import SkillManager

mgr = SkillManager()
mgr.discover()

# Archive
mgr.archive_skill("csv-analysis")
print("csv-analysis" in mgr.skill_names)  # False — removed from index

# Restore
mgr.restore_skill("csv-analysis")
mgr.discover()                             # re-index after restore
print("csv-analysis" in mgr.skill_names)  # True

result = mgr.rollback_skill("csv-analysis")
# {"success": False, "error": "No rollback snapshot for skill 'csv-analysis'"}

from praisonaiagents import Agent, SkillManager

# Agent creates and improves skills over time
agent = Agent(
    name="Self-Improving Agent",
    instructions="""
    When you learn something new, create a skill for it.
    When a skill becomes outdated, archive it.
    """,
    tools=["skill_manage", "skills_list"]
)

# The agent's skill_manage calls automatically:
# 1. stamp created-at, use-count, patch-count on creation
# 2. increment use-count on each use
# 3. archive (not delete) when retiring a skill
agent.start("Learn how to summarise weekly reports, then use that knowledge.")

from praisonaiagents import SkillManager

mgr = SkillManager()
mgr.discover()

def safe_edit(skill_name: str, new_content: str) -> bool:
    result = mgr.edit_skill(skill_name, new_content)
    if not result["success"]:
        print(f"Edit failed: {result['error']}")
        return False

    # Verify the skill still activates correctly
    instructions = mgr.get_instructions(skill_name)
    if instructions is None:
        print("Skill broken after edit — rolling back")
        mgr.rollback_skill(skill_name)
        return False

    return True

safe_edit("csv-analysis", "# CSV Analysis v2\nImproved steps...")

from praisonaiagents import SkillManager

mgr = SkillManager()
mgr.discover()

STALE_THRESHOLD_DAYS = 30

for skill in mgr.skills:
    props = skill.properties
    idle = props.idle_days

    print(f"{props.name}:")
    print(f"  agent-created : {getattr(props, 'agent_created', False)}")
    print(f"  use-count     : {getattr(props, 'use_count', 0)}")
    print(f"  last-used     : {getattr(props, 'last_used', None)}")
    print(f"  patch-count   : {getattr(props, 'patch_count', 0)}")
    print(f"  idle-days     : {idle}")

    if idle is not None and idle > STALE_THRESHOLD_DAYS:
        print(f"  → STALE: archiving")
        mgr.archive_skill(props.name)