data

name	data
description	Raw data storage layer for 1ai-skills. Provides structured data persistence, query interface, and data pipeline support for skill operations. history. Use when working with data.
domain	meta
author	oyi77
license	Apache-2.0
subdomain	meta-skills
tags	["data","meta-learning","self-improvement","skill-evolution"]
persona	{"name":"Database Architect","expertise":"SQLite, data modeling, query optimization","philosophy":"Data is the foundation of intelligence"}
version	1.0.0

Data

When to Use

Trigger phrases:

• "data"
• "Help me with data"

Use cases:

• When the task matches this skill's domain expertise

When NOT to use:

• For tasks outside this skill's scope

record_execution - record one skill execution
/meta-datastore record-execution --skill seo-optimizer --latency 245 --success

# Query performance
/meta-datastore query "SELECT AVG(latency_ms) FROM skill_executions WHERE skill_name='seo-optimizer'"

# Get improvement candidates
/meta-datastore get-improvements --min-impact 0.7 --status proposed

Code Examples

Storing a skill execution record

import sqlite3
import hashlib
from datetime import datetime, timezone
from pathlib import Path

DB_PATH = "~/.1ai/data/store.sqlite"

def _expand_path(p: str) -> str:
    return p.replace("~", str(Path.home())) if "~" in p else p

def record_execution(skill_name: str, latency_ms: float, success: bool,
                     error_class: str = "", output_summary: str = "",
                     session_id: str = "") -> str:
    """Insert one skill execution record. Returns the execution_id."""
    ts = datetime.now(timezone.utc).isoformat()
    exec_id = hashlib.sha256(
        .encode()
    ).hexdigest()[:]
    conn = sqlite3.connect(_expand_path(DB_PATH))
    conn.execute()
    :
        conn.execute(, (exec_id, skill_name, ts, latency_ms,
                success  , error_class,
              output_summary[:], session_id))
        conn.commit()
    :
        conn.close()
     exec_id