Add !status command and web search tool

- !status: shows agent count, load, RAM, disk, uptime, Ollama model loaded
- web_search tool: agents can search via SearXNG (searx.mymx.me)
  Works in both structured and text-based tool call paths

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

agent/agent.py

@@ -104,8 +104,31 @@ TOOLS = [
             },
         },
     },
+    {
+        "type": "function",
+        "function": {
+            "name": "web_search",
+            "description": "Search the web using SearXNG. Returns titles, URLs, and snippets for the top results. Use this when you need current information or facts you're unsure about.",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "query": {
+                        "type": "string",
+                        "description": "The search query",
+                    },
+                    "num_results": {
+                        "type": "integer",
+                        "description": "Number of results to return (default 5)",
+                    },
+                },
+                "required": ["query"],
+            },
+        },
+    },
 ]
 
+SEARX_URL = CONFIG.get("searx_url", "https://searx.mymx.me")
+
 
 def log(msg):
     print(f"[agent:{NICK}] {msg}", flush=True)
@@ -219,6 +242,32 @@ def save_memory(topic, content):
     return f"Memory saved to {filepath}"
 
 
+def web_search(query, num_results=5):
+    """Search the web via SearXNG."""
+    log(f"Web search: {query[:60]}")
+    try:
+        import urllib.parse
+        params = urllib.parse.urlencode({"q": query, "format": "json"})
+        req = urllib.request.Request(
+            f"{SEARX_URL}/search?{params}",
+            headers={"User-Agent": "fireclaw-agent"},
+        )
+        with urllib.request.urlopen(req, timeout=15) as resp:
+            data = json.loads(resp.read())
+        results = data.get("results", [])[:num_results]
+        if not results:
+            return "No results found."
+        lines = []
+        for r in results:
+            title = r.get("title", "")
+            url = r.get("url", "")
+            snippet = r.get("content", "")[:150]
+            lines.append(f"- {title}\n  {url}\n  {snippet}")
+        return "\n".join(lines)
+    except Exception as e:
+        return f"[search error: {e}]"
+
+
 def try_parse_tool_call(text):
     """Try to parse a text-based tool call from model output.
     Handles formats like:
@@ -298,6 +347,12 @@ def query_ollama(messages):
                     log(f"Tool call [{round_num+1}/{MAX_TOOL_ROUNDS}]: save_memory({topic})")
                     result = save_memory(topic, content)
                     messages.append({"role": "tool", "content": result})
+                elif fn_name == "web_search":
+                    query = fn_args.get("query", "")
+                    num = fn_args.get("num_results", 5)
+                    log(f"Tool call [{round_num+1}/{MAX_TOOL_ROUNDS}]: web_search({query[:60]})")
+                    result = web_search(query, num)
+                    messages.append({"role": "tool", "content": result})
                 else:
                     messages.append({
                         "role": "tool",
@@ -324,6 +379,12 @@ def query_ollama(messages):
                 log(f"Text tool call [{round_num+1}/{MAX_TOOL_ROUNDS}]: save_memory({topic})")
                 result = save_memory(topic, mem_content)
                 messages.append({"role": "user", "content": f"{result}\n\nNow respond to the user."})
+            elif fn_name == "web_search":
+                query = fn_args.get("query", "")
+                num = fn_args.get("num_results", 5)
+                log(f"Text tool call [{round_num+1}/{MAX_TOOL_ROUNDS}]: web_search({query[:60]})")
+                result = web_search(query, num)
+                messages.append({"role": "user", "content": f"Search results:\n{result}\n\nNow respond to the user based on these results."})
             payload["messages"] = messages
             continue
 
@@ -339,7 +400,8 @@ def build_messages(question, channel):
     if TOOLS_ENABLED:
         system += "\n\nYou have access to tools:"
         system += "\n- run_command: Execute shell commands on your system."
-        system += "\n- save_memory: Save important information to your persistent workspace (/workspace/memory/). Use this to remember things across restarts — user preferences, learned facts, project context."
+        system += "\n- web_search: Search the web for current information."
+        system += "\n- save_memory: Save important information to your persistent workspace."
         system += "\nUse tools when needed rather than guessing. Your workspace at /workspace persists across restarts."
     if AGENT_MEMORY and AGENT_MEMORY != "# Agent Memory":
         system += f"\n\nIMPORTANT - Your persistent memory (facts you saved previously, use these to answer questions):\n{AGENT_MEMORY}"

src/overseer.ts

@@ -153,8 +153,50 @@ export async function runOverseer(config: OverseerConfig) {
           break;
         }
 
+        case "!status": {
+          try {
+            const os = await import("node:os");
+            const { execFileSync } = await import("node:child_process");
+            const agents = listAgents();
+            const uptime = Math.floor(os.uptime() / 3600);
+            const totalMem = (os.totalmem() / 1e9).toFixed(0);
+            const freeMem = (os.freemem() / 1e9).toFixed(0);
+            const load = os.loadavg()[0].toFixed(2);
+
+            // Disk free
+            let diskFree = "?";
+            try {
+              const dfOut = execFileSync("df", ["-h", "/"], { encoding: "utf-8" });
+              const parts = dfOut.split("\n")[1]?.split(/\s+/);
+              if (parts) diskFree = `${parts[3]} free / ${parts[1]}`;
+            } catch {}
+
+            // Ollama model loaded
+            let ollamaModel = "none";
+            try {
+              const http = await import("node:http");
+              const psData = await new Promise<string>((resolve, reject) => {
+                http.get("http://localhost:11434/api/ps", (res) => {
+                  const chunks: Buffer[] = [];
+                  res.on("data", (c) => chunks.push(c));
+                  res.on("end", () => resolve(Buffer.concat(chunks).toString()));
+                }).on("error", reject);
+              });
+              const running = JSON.parse(psData).models;
+              if (running?.length > 0) {
+                ollamaModel = running.map((m: { name: string }) => m.name).join(", ");
+              }
+            } catch {}
+
+            bot.say(event.target, `Agents: ${agents.length} running | Load: ${load} | RAM: ${freeMem}/${totalMem} GB free | Disk: ${diskFree} | Uptime: ${uptime}h | Ollama: ${ollamaModel}`);
+          } catch (e) {
+            bot.say(event.target, "Error getting status.");
+          }
+          break;
+        }
+
         case "!help": {
-          bot.say(event.target, "Commands: !invoke <template> [name] | !destroy <name> | !list | !model <name> <model> | !models | !templates | !help");
+          bot.say(event.target, "Commands: !invoke <template> [name] | !destroy <name> | !list | !model <name> <model> | !models | !templates | !status | !help");
           break;
         }
       }