feat(python): add zeroclaw-tools companion package for LangGraph tool calling

- Add Python package with LangGraph-based agent for consistent tool calling
- Provides reliable tool execution for providers with inconsistent native support
- Includes tools: shell, file_read, file_write, web_search, http_request, memory
- Discord bot integration included
- CLI tool for quick interactions
- Works with any OpenAI-compatible provider (Z.AI, OpenRouter, Groq, etc.)

Why: Some LLM providers (e.g., GLM-5/Zhipu) have inconsistent tool calling behavior.
LangGraph's structured approach guarantees reliable tool execution across all providers.

python/zeroclaw_tools/tools/memory.py

@@ -0,0 +1,86 @@
+"""
+Memory storage tools for persisting data between conversations.
+"""
+
+import json
+import os
+from pathlib import Path
+
+from langchain_core.tools import tool
+
+
+def _get_memory_path() -> Path:
+    """Get the path to the memory storage file."""
+    return Path.home() / ".zeroclaw" / "memory_store.json"
+
+
+def _load_memory() -> dict:
+    """Load memory from disk."""
+    path = _get_memory_path()
+    if not path.exists():
+        return {}
+    try:
+        with open(path, "r") as f:
+            return json.load(f)
+    except Exception:
+        return {}
+
+
+def _save_memory(data: dict) -> None:
+    """Save memory to disk."""
+    path = _get_memory_path()
+    path.parent.mkdir(parents=True, exist_ok=True)
+    with open(path, "w") as f:
+        json.dump(data, f, indent=2)
+
+
+@tool
+def memory_store(key: str, value: str) -> str:
+    """
+    Store a key-value pair in persistent memory.
+
+    Args:
+        key: The key to store under
+        value: The value to store
+
+    Returns:
+        Confirmation message
+    """
+    try:
+        data = _load_memory()
+        data[key] = value
+        _save_memory(data)
+        return f"Stored: {key}"
+    except Exception as e:
+        return f"Error: {e}"
+
+
+@tool
+def memory_recall(query: str) -> str:
+    """
+    Search memory for entries matching the query.
+
+    Args:
+        query: The search query
+
+    Returns:
+        Matching entries or "no matches" message
+    """
+    try:
+        data = _load_memory()
+        if not data:
+            return "No memories stored yet"
+
+        query_lower = query.lower()
+        matches = {
+            k: v
+            for k, v in data.items()
+            if query_lower in k.lower() or query_lower in str(v).lower()
+        }
+
+        if not matches:
+            return f"No matches for: {query}"
+
+        return json.dumps(matches, indent=2)
+    except Exception as e:
+        return f"Error: {e}"